There's an odd trend with these sorts of posts where the author claims to have had some transformative change in their workflow brought upon by LLM coding tools, but also seemingly has nothing to show for it. To me, using the most recent ChatGPT Codex (5.3 on "Extra High" reasoning), it's incredibly obvious that while these tools are surprisingly good at doing repetitive or locally-scoped tasks, they immediately fall apart when faced with the types of things that are actually difficult in software development and require non-trivial amounts of guidance and hand-holding to get things right. This can still be useful, but is a far cry from what seems to be the online discourse right now.
As a real world example, I was told to evaluate Claude Code and ChatGPT codex at my current job since my boss had heard about them and wanted to know what it would mean for our operations. Our main environment is a C# and Typescript monorepo with 2 products being developed, and even with a pretty extensive test suite and a nearly 100 line "AGENTS.md" file, all models I tried basically fail or try to shortcut nearly every task I give it, even when using "plan mode" to give it time to come up with a plan before starting. To be fair, I was able to get it to work pretty well after giving it extremely detailed instructions and monitoring the "thinking" output and stopping it when I see something wrong there to correct it, but at that point I felt silly for spending all that effort just driving the bot instead of doing it myself.
It almost feels like this is some "open secret" which we're all pretending isn't the case too, since if it were really as good as a lot of people are saying there should be a massive increase in the number of high quality projects/products being developed. I don't mean to sound dismissive, but I really do feel like I'm going crazy here.
I tend to be surprised in the variance of reported experiences with agentic flows like Claude Code and Codex CLI.
It's possible some of it is due to codebase size or tech stack, but I really think there might be more of a human learning curve going on here than a lot of people want to admit.
I think I am firmly in the average of people who are getting decent use out of these tools. I'm not writing specialized tools to create agents of agents with incredibly detailed instructions on how each should act. I haven't even gotten around to installing a Playwright mcp (probably my next step).
But I've:
- created project directories with soft links to several of my employer's repos, and been able to answer several cross-project and cross-team questions within minutes, that normally would have required "Spike/Disco" Jira tickets for teams to investigate
- interviewed codebases along with product requirements to come up with very detailed Jira AC, and then,.. just for the heck of it, had the agent then use that AC to implement the actual PR. My team still code-reviewed it but agreed it saved time
- in side projects, have shipped several really valuable (to me) features that would have been too hard to consider otherwise, like... generating pdf book manuscripts for my branching-fiction creating writing club, and launching a whole new website that has been mired in a half-done state for years
Really my only tricks are the basics: AGENTS.md, brainstorm with the agent, continually ask it to write markdown specs for any cohesive idea, and then pick one at a time to implement in commit-sized or PR-sized chunks. GPT-5.2 xhigh is a marvel at this stuff.
My codebases are scala, pekko, typescript/react, and lilypond - yeah, the best models even understand lilypond now so I can give it a leadsheet and have it arrange for me two-hand jazz piano exercises.
I generally think that if people can't reach the above level of success at this point in time, they need to think more about how to communicate better with the models. There's a real "you get out of it what you put into it" aspect to using these tools.
I can’t speak for anyone else, but Claude Code has been transformative for me.
I can’t say it’s led to shipping “high quality projects”, but it has let me accomplish things I just wouldn’t have had time for previously.
I’ve been wanting to develop a plastic -> silicone -> plaster -> clay mold making process for years, but it’s complex and mold making is both art and science. It would have been hundreds of hours before, with maybe 12 hours of Claude code I’m almost there (some nagging issues… maybe another hour).
And I had written some home automation stuff back with Python 2.x a decade ago; it was never worth the time to refamiliarize myself with in order to update, which led to periodic annoyances. 20 minutes, and it’s updated to all the latest Python 3.x and modern modules.
For me at least, the difference between weeks and days, days and hours, and hours and minutes has allowed me to do things I just couldn’t justify investing time in before. Which makes me happy!
So maybe some folks are “pretending”, or maybe the benefits just aren’t where you’re expecting to see them?
I’m trying to pivot my career from web/business app dev entirely into embedded, despite the steep learning curve, many new frameworks and tool chains, because I now have a full-time infinitely patient tutor, and I dare say it’s off to a pretty good start so far.
You're not going crazy. That is what I see as well. But, I do think there is value in:
- driving the LLM instead of doing it yourself. - sometimes I just can't get the activation energy and the LLM is always ready to go so it gives me a kickstart
- doing things you normally don't know. I learned a lot of command like tools and trucks by seeing what Claude does. Doing short scripts for stuff is super useful. Of course, the catch here is if you don't know stuff you can't drive it very well. So you need to use the things in isolation.
- exploring alternative solutions. Stuff that by definition you don't know. Of course, some will not work, but it widens your horizon
- exploring unfamiliar codebases. It can ingest huge amounts of data so exploration will be faster. (But less comprehensive than if you do it yourself fully)
- maintaining change consistency. This I think it's just better than humans. If you have stuff you need to change at 2 or 3 places, you will probably forget. LLM's are better at keeping consistency at details (but not at big picture stuff, interestingly.)
For me the biggest benefit from using LLMs is that I feel way more motivated to try new tools because I don't have to worry about the initial setup.
I'd previously encountered tools that seemed interesting, but as soon as I tried getting it to run I found myself going down an infinite debugging hole. With an LLM I can usually explain my system's constraints and the best models will give me a working setup from which I can begin iterating. The funny part is that most of these tools are usually AI related in some way, but getting a functional environment often felt impossible unless you had really modern hardware.
Same. This weekend, I built a Flutter app and a Wails app just to compare the two. Would have never done either on my own due to the up front boilerplate— and not knowing (nor really wishing to know) Dart.
> - maintaining change consistency. This I think it's just better than humans. If you have stuff you need to change at 2 or 3 places, you will probably forget. LLM's are better at keeping consistency at details (but not at big picture stuff, interestingly.)
I use Claude Code a decent amount, and I actually find that sometimes this can be the opposite for me. Sometimes it is actually missing other areas that the change will impact and causing things to break. Sometimes when I go to test it I need to correct it and point out it missed something or I notice when in the planning phase that it is missing something.
However I do find if you use a more powerful opus model when planning, it does consider things fully a lot better than it used to. This is actually one area I have been seeing some very good improvements as the models and tooling improves.
In fact, I actually hope that these AI tools keep getting better at the point you mention, as humans also have a "context limit". There are only so many small details I can remember about the codebase so it is good if AI can "remember" or check these things.
I guess a lot of the AI can also depend on your codebase itself, how you prompt it, and what kind of agents file you have. If you have a robust set of tests for your application you can very easily have AI tools check their work to ensure things aren't being broken and quickly fix it before even completing the task. If you don't have any testing more could be missed. So I guess it's just like a human in some sense. If you have a crappy codebase for the AI to work with, the AI may also sometimes create sloppy work.
>driving the LLM instead of doing it yourself. - sometimes I just can't get the activation energy and the LLM is always ready to go so it gives me a kickstart
There is a counter issue though, realizing mid session that the model won’t be able to deliver that last 10%, and now you have to either grok a dump of half finished code or start from scratch.
Some? I'd be shocked if it's less than 70% of everything AI-related in here.
For example a lot of pro-OpenAI astroturfing really wanted you to know that 5.3 scored better than opus on terminal-bench 2.0 this week, and a lot of Anthropic astroturfing likes to claim that all your issues with it will simply go away as soon as you switch to a $200/month plan (like you can't try Opus in the cheaper one and realise it's definitely not 10x better).
Frankly, it sounds like you have a lot to learn about agentic coding. It’s hard to define exactly what makes some of us so good at using it, and others so poor, but agentic coding has been life changing for myself and the folks I’ve tutored on its use. We’re all using the same tools, but subtle differences can make a big difference.
Pretty much every software engineer I've talked to sees it more or less like you do, with some amount of variance on exactly where you draw the line of "this is where the value prop of an LLM falls off". I think we're just awash in corporate propaganda and the output of social networks, and "it's good for certain things, mixed for others" is just not very memetic.
I wish this was true. My experience is co-workers who do lip service as to treating LLM like a baby junior dev, only to near-vibe every feature and entire projects, without spending so much as 10 mins to think on their own first.
At my work I interview a lot of fresh grads and interns. I have been doing that consistently for last 4 years. During the interviews I always ask the candidates to show and tell, share their screen and talk about their projects and work at school and other internships.
Since last few months, I have seen a notable difference in the quality and extent of projects these students have been able to accomplish. Every project and website they show looks polished, most of those could be a full startup MVP pre AI days.
The bar has clearly been raised way high, very fast with AI.
I’ve had the same experience with the recent batch of candidates for a Junior Software Engineer position we just filled. Their projects looked impressive on the surface and seemed very promising.
Once we got them into a technical screening, most fell apart writing code. Our problem was simple: using your preferred programming language, model a shopping cart object that has the ability to add and remove items from the cart and track the cart total.
We were shocked by how incapable most candidates were in writing simple code without their IDEs tab completion capability. We even told them to use whatever resources they normally used.
In my opinion, it has always been the “easy” part of development to make a thing work once. The hard thing is to make a thousand things work together over time with constantly changing requirements, budgets, teams, and org structures.
For the former, greenfield projects, LLMs are easily a 10x productivity improvement. For the latter, it gets a lot more nuanced. Still amazingly useful in my opinion, just not the hands off experience that building from scratch can be now.
> ... but also seemingly has nothing to show for it
This x1000, I find it so ridiculous.
usually when someone hypes it up it's things like, "i have it text my gf good morning every day!!", or "it analyzed every single document on my computer and wrote me a poem!!"
Matches my experience pretty well. FWIW, this is the opinion that I hear most frequently in real life conversation. I only see the magical revelation takes online -- and I see a lot of them.
I think it’s just very alien in that things which tend to be correlated in humans may not be so correlated in LLMs. So two things that we expect people to be similarly good at end up being very different in an AI.
It does also seem to me that there is a lot of variance in skills for prompting/using AI in general (I say this as someone who is not particularly good as far as I’m aware – I’m not trying to keep tips secret from you). And there is also a lot of variance in the ability for an AI to solve problem of equal difficulty for a human.
I find these agents incredibly useful for eliminating time spent on writing utility scripts for data analysis or data transformation.
But... I like coding, getting relegated to being a manager 100%? Sounds like a prison to me not freedom.
That they are so good at the things I like to do the least and still terrible at the things at which I excel. That's just gravy.
But I guess this is in line with how most engineers transition to management sometime in their 30s.
> if it were really as good as a lot of people are saying there should be a massive increase in the number of high quality projects/products being developed.
The headline gain is speed. Almost no-one's talking about quality - they're moving too fast to notice the lack.
The pattern matching and absence or real thinking is still strong.
Tried to move some excel generation logic from epplus to closedxml library.
ClosedXml has basically the same API so the conversion was successful. Not a one-shot but relatively easy with a few manual edits.
But closedxml has no batch operations (like apply style to the entire column): the api is there but internal implementation is on cell after cell basis. So if you have 10k rows and 50 columns every style update is a slow operation.
Naturally, told all about this to codex 5.3 max thinking level. The fucker still succumbed to range updates here and there.
Told it explicitly to make a style cache and reuse styles on cells on same y axis.
5-6 attempts — fucker still tried ranges here and there. Because that is what is usually done.
Maybe it is language specific? Maybe LLMs have a lot of good JavaScript/TypeScript samples for training and it works for those devs (e.g. me). I heard that Scala devs have problems with LLMs writing code too. I am puzzled by good devs not managing to get LLM work for them.
I definitely think it's language specific. My history may deceive me here, but i believe that LLMs are infinitely better at pumping out python scripts than java. Now i have much, much more experience with java than python, so maybe it's just a case of what you don't know.... However, The tools it writes in python just work for me, and i can incrementally improve them and the tools get rationally better and more aligned with what i want.
I then ask it to do the same thing in java, and it spends a half hour trying to do the same job and gets caught in some bit of trivia around how to convert html escape characters, for instance, s.replace("<", "<").replace(">", ">").replace("\"").replace("""); as an example and endlessly compiles and fails over and over again, never able to figure out what it has done wrong, nor decides to give up on the minutia and continue with the more important parts.
I remember when Anthropic was running their Built with Claude contest on reddit. The submissions were few and let's just say less than impressive. I use Claude Code and am very pro-AI in general, but the deeper you go, the more glaring the limitations become. I could write an essay about it, but I feel like there's no point in this day and age, where floods of slop in fractured echo chambers dominate.
I always find that characterization of Grey and the Cortex podcast to be weird. He never claims to be a productivity master or the most productive person around. Quite the opposite, he has said multiple times how much he is not naturally productive, and how he actually kinda dislikes working in general. The systems and habits are the ways he found to essentially trick himself into working.
Which I think is what people gather from him, but somehow think he's hiding it or pretending is not the case? Which I find strange, given how openly he's talked about it.
As for his productivity going down over time, I think that's a combination of his videos getting bigger scopes and production values, and also he moving some of his time into some not so publicly visible ventures. E.g., he was one of the founders of Standard, which eventually became the Nebula streaming service (though he left quite a while ago now).
The crazy pills you are taking is that thinking people have anything to prove to you. The C compiler that Anthropic created or whatever verb your want to use should prove that Claude is capable of doing reasonably complex level of making software. The problem is people have egos, myself included. Not in the inflated sense, but in the "I built a thing a now the Internet is shitting on me and I feel bad" sense. There's fundcli and nitpick on my GitHub that I created using Claude. fundcli looks at your shell history and suggests places to donate to, to support open source software you actually use. Nitpick is a TUI HN client. I've shipped others. The obvious retort is that those two things aren't "real" software; they're not complex, they're not making me any money. In fact, fundcli is costing me piles of money! As much as I can give it! I don't need anyone to tell me that or shit on the stuff I'm building.
The "open secret" is that shipping stuff is hard. Who hasn't bought a domain name for a side project that didn't go anywhere. If there's anybody out there, raise your hand! So there's another filtering effect.
The crazy pills are thinking that HN is in any way representative of anything about what's going on in our broader society. Those projects are out there, why do you assume you'll be told about it? That someone's going to write an exposé/blog post on themselves about how they had AI build a thing and now they're raking in the dollars and oh, buy my course on learning how to vibecode? The people selling those courses aren't the ones shipping software!
> The C compiler that Anthropic created or whatever verb your want to use should prove that Claude is capable of doing reasonably complex level of making software.
I don't doubt that an LLM would theoretically be capable of doing these sorts of things, nor did I intend to give off that sentiment, rather I was more evaluating if it was as practical as some people seem to be making the case for. For example, a C compiler is very impressive, but its clear from the blog post[0] that this required a massive amount of effort setting things up and constant monitoring and working around limitations of Claude Code and whatnot, not to mention $20,000. That doesn't seem at all practical, and I wonder if Nicholas Carlini (the author of the Anthropic post) would have had more success using Claude Code alongside his own abilities for significantly cheaper. While it might seem like moving the goalpost, I don't think it's the same thing to compare what I was saying with the fact that a multi billion dollar corporation whose entire business model relies on it can vibe code a C compiler with $20,000 worth of tokens.
> The problem is people have egos, myself included. Not in the inflated sense, but in the "I built a thing a now the Internet is shitting on me and I feel bad" sense.
Yes, this is actually a good point. I do feel like there's a self report bias at play here when it comes to this too. For example, someone might feel like they're more productive, but their output is roughly the same as what it was pre-LLM tooling. This is kind of where I'm at right now with this whole thing.
> The "open secret" is that shipping stuff is hard. Who hasn't bought a domain name for a side project that didn't go anywhere. If there's anybody out there, raise your hand! So there's another filtering effect.
My hand is definitely up here, shipping is very hard! I would also agree that it's an "open secret", especially given that "buying a domain name for a side project that never goes anywhere" is such a universal experience.
I think both things can be true though. It can be true that these tools are definitely a step up from traditional IDE-style tooling, while also being true that they are not nearly as good as some would have you believe. I appreciate the insight, thanks for replying.
If people make extraordinary claims, I expect extraordinary proofs…
Also, there is nothing complex in a C compiler. As students we built these things as toy projects at uni, without any knowledge of software development practices.
> The reality: 3 weeks in, ~50 hours of coding, and I'm mass-producing features faster than I can stabilize them. Things break. A lot. But when it works, it works.
> it's incredibly obvious that while these tools are surprisingly good at doing repetitive or locally-scoped tasks, they immediately fall apart when faced with the types of things that are actually difficult in software development and require non-trivial amounts of guidance and hand-holding to get things right
I used this line for a long time, but you could just as easily say the same thing for a typical engineer. It basically boils down to "Claude likes its tickets to be well thought out". I'm sure there is some size of project where its ability to navigate the codebase starts to break down, but I've fed it sizeable ones and so long as the scope is constrained it generally just works nowadays
The difference is a real engineer will say "hey I need more information to give you decent output." And when the AI does do that, congrats, the time you spend identifying and explaining the complexity _is_ the hard time consuming work. The code is trivial once you figure out the rest. The time savings are fake.
I have always failed to understand the obsessive dream of many engineers to become managers. It seems not to have to do merely with an increase in revenue.
Is it really to escape from "getting bogged down in the specifics" and being able to "focus on the higher-level, abstract work", to quote OP's words? I thought naively that engineering always has been about dealing with the specifics and the joy of problem solving. My guess is that the drive is toward power. Which is rather natural, if you think about it.
Science and the academic world
I have always failed to understand the obsessive dream of many engineers to become managers. It seems not to be merely about an increase in revenue.
Is it to escape from "getting bogged down in the specifics" and being able to "focus on the higher-level, abstract work", to quote OP's words? I thought naively that engineering has always been about dealing with the specifics and the joy of problem-solving. My guess is that the drive is towards power, which is rather natural, if you think about it.
Science and the academic world suffer a comparable plague.
Don't you get bored with spending many years learning and becoming advanced or an expert in a system paradigm (like different hosting systems), a programming language (i.e. Perl), or a framework (pick your JS framework), only to have it completely obsoleted a few years later? And then in a job interview, when you try to sell yourself on your wisdom as expert on thing X, new to Y, they dismiss you because the 25 year old has been using Y since its release three years ago?
And when you're in an existing company, stuck in thing X, knowing that it's obsolete, and the people doing the latest Y that's hot in the job market are in another department and jealously guard access to Y projects?
How about when you go to interview, and you not ONLY have to know Y, but the Leetcode from 15 years ago?
So maybe I've given you another alternative to 'it has to be power, there's no other rational reason to go into management'.
Here's a gentler one: if you want to build big things, involving many people, you need to be in management.
Do you enjoy brick laying and calculating angles around doorways? You're the engineer. Do you want to be the architect hiring engineers, working with project managers, and assessing the budget while worrying about approvals? They're different types of work, and it's not about 'power' like you are suggesting. Autonomy and decision-making power are more the 'power' engineers often don't get (unless they are lucky, very very smart or in a small startup-like environment).
N=1 but I do love constantly learning new things, and building small, purposeful, tailored products with small groups of people.
I've gone back and forth across the lead and management lines many times now, and it is career limiting in many many ways. But it's too fulfilling to give up. And I swear there is magic in what small, expert groups are able to produce that laps large org on the regular.
From my (limited) experience, that magic is incredibly linked to autonomy and ownership.
Some research around British government workers found higher job satisfaction in units with hands-off managers. It resonates with my own career. I’m really excited and want to go to work when I’m on a small, autonomous team with little red tape and politics. Larger orgs simply can’t — or haven’t — ever offered me the same feeling; with some exceptions in Big 3 consulting if I was the expert on a case.
As a manager, I love being hands-off - I like directs that take ownership and I try to give people projects and roles that they want. They use their creativity and I help unblock, expand, course correct or suggest as needed. It saves them from the politics and they get high level mentoring.
The worst manager is the micromanager - either because he's nervous about his job security, because he doesn't know how to delegate, or because he's been hands-on forever and can't let go.
isn't that more a question of company size and industry (i.e. less regulated than healthcare and financial services) than whether management is good or bad?
I don't see why it contradicts my little rant above. Of course I also prefer small, nimble teams with lots of autonomy, with individuals who thrive being delegated only extremely broad tasks. The only part where I think there's a difference is the constantly learning.
I love constantly learning. My issue isn't that. It's that I don't want to HAVE to constantly be practicing at home and on the weekend. I did this in my 20s and I can't/won't do this anymore. I just have no time or energy now as an Old.
I don't really think management is good or bad, just different, and not really for me. The management career ladder though I do feel goes higher in large organizations than small.
For myself it is the hands-on work I find most fulfilling unfortunately. I have some sort of brain worm that makes me want to practice all the new things at home/weekend if work isn't letting me. I'm sure it'll burn me out at some point, but to paraphrase a famous creep: I keep getting older, my brainworm stays the same age.
I don't think having to practice at home and at weekends is necessarily a part of engineering though. Every place I've worked at, there have been ample opportunities to keep up-to-date on paid hours, be that in conferences, learning materials, trying out side projects or weird ideas in more niche technologies, etc.
I think if you have a job that gives you the chance to expand your skills, pick new tech with the ability and time to learn onsite, and offers you that grace, that's a great company to work for.
Within my power I try to do that with my directs, making sure new interesting things are cycled in so their CVs become stronger. But me, personally, I've had really bad luck with this. I always had to study on the weekends for something that either isn't used in my company or someone else jealously guards because it's hot on the market.
> only to have it completely obsoleted a few years later
Not really. There aren’t as many fundamentally new ideas in modern tech as it may seem.
Web servers have existed for more than 30 years and haven’t changed that much since then. Or e.g., React + Redux is pretty much the same thing as WinProc from WinAPI - invented some time in ~1990. Before Docker, there were Solaris Zones and FreeBSD jails. TCP/IP is 50 years old. And many, many other things we perceive as new.
Moreover, I think it’s worth looking back and learning some of the “old tech” for inspiration; there’s a wealth of deep and prescient ideas there. We still don’t have a full modern equivalent of Macromedia Flash, for example.
>only to have it completely obsoleted a few years later
Almost nothing goes obsolete in software; it just becomes unpopular. You can still write every website you see on the Internet with just jQuery. There are perfectly functional HTTP frameworks for Cobol.
You might be right about a Leetcode effect and the difficulty to find new interesting positions. But OP wasn't stressing that at all but the desire to architect and manage. I might have put to much emphasis of the managing and too less on the urge to architect and see things from above. I agree.
I am scientist and worked from time to time as a research engineer merely to pay the bills, so I may see things differently. I always like doing lab / field work and first-hand data analysis. Many engineers I know would likely never stop tinkering and building stuff. It may be easier for a scientist than for an engineer to still get trilled, I don't know.
> Do you enjoy brick laying and calculating angles around doorways? You're the engineer. Do you want to be the architect hiring engineers, working with project managers, and assessing the budget while worrying about approvals?
These are inherently different levels of power. I'm not sure how your example is supposed to be the opposite when you compare someone laying bricks to someone making hiring and firing decisions about groups of people. Your scenario is fundamentally a power imbalance
A rare occurrence these days. I suppose a lot of it has to do with shrinking attention spans and instant gratification and the lack of effort required to do so many things that required even a little bit of effort before
In my opinion, time spent learning Perl or an outmoded framework still helped me learn new things and stretch myself. A lot of that knowledge is transferable to other languages or frameworks. After learning QuickBasic and REXX it was pretty easy to pickup Ruby and Python. ;-)
And I would argue that what you are describing is why we end up in a system where the people who are talented and have in depth knowledge end up in "dumber ~ managerial" roles and we end up losing real talent and knowledge because of the incentives you explicitly describe.
If only the world incentivized ICs with depth of knowledge to stay in those roles for the long haul instead of chopping off our knowledge of specificity at the apex of their depth of knowledge. So many managers have no talent, no depth of knowledge and a passable ability to manage people.
Thank you for adding color. This is the exact reason why I want to get in to management. Sadly, I am just not cut out to manage people. Nowadays, my role is more of a hybrid between Principal and EM, which may be awkward at times. If it weren't for excellent PM & PgM, I'd be stretching myself too thin.
It's a skill that takes practice -coordinating disparate people and groups, creating communication where you notice they're not talking to each other, creating or fixing processes that annoy or cause chaos if they're not there, encouraging people, being a therapist, seeing what's not there and pushing a vision while you get the group to go along, protecting people from management above and pressures around, etc are mostly skills that you learn.
Sometimes no one will give you feedback so you have to figure it out yourself (unless you're lucky to get a mentor), so you just have to throw yourself in and give yourself grace to fail and succeed over time.
The only skill of these I think is possibly genetic or innate, is being able to see the big picture and make strategical decisions. A lot of tech people skew cognitively in narrow areas, and have trouble conceptualizing the world beyond.
One challenge here is the ubiquitous 'managers just approve vacations and waste space' sentiment on here and in some places. These people are a chore to manage (and sometimes are better not being present in your group).
Since when do your line managers choose to stack rank?
Do you know what stank ranking even is and where it comes from? If you have to rate your group from 1 to 5, each individual, and you rate them all 4s and 5s, they crack down and force you to select a 2 and a 3 and only have one 5. Now, would you prefer a CFO, CTO or even a project manager be the one to do it? It's a weird comment.
Re-read and think about what was written - the 2s aren'tcoming from the line managers, you're barking up the wrong tree in the stack ranking process. I just explained that stack ranking gets scaled and adjusted by the brass, and I just in this example rated everyone a 4 and 5.
Again, as an older manager today, I can see myself in my 20s in the resistance and stubbornness to 'how corporations work' espoused in comments like yours. I sympathize, but I warn you against being naive and ideological, because unfortunately human groups be human groups, and organizations for better or for worse behave in predictable patterns. You might as well know as much as possible so you can deal with it better.
Weirder that you think software couldn’t get built without a CFO. The GP comment was noting that management is an outcome of capital wanting more control, not because many layers of middle managers is a naturally optimal way to complete software projects
CFOs manage budgets and funding and things tech people don't. I hate to parrot your tone but, weirder that you think software can be built in a company without there being a budget of some kind.
I have worked at organizations where most engineering and many product decisions were made bottom-up, through written RFDs and ADRs, and horizontal conversations between lead, staff and principal engineers. The tradeoff is that it can take weeks, months or years to both agree or schedule work on larger projects, where other (especially small) organizations might take hours to weeks.
I actually don’t think the author wants to become a real manager, he wants to play a video game where he sends NPCs around to do stuff.
Real managers deal with coaching, ownership, feelings, politics, communication, consensus building, etc. The people who are good at it like setting other people up to win.
As a manager who is trying to do all the things you listed well, I would love it to be more like a game sending NPCs around. Ignoring the macro implications of AI, even if very successful at or resistant to it, I’d think there would be very, very few people who are actively seeking people drama. Educating kids can be fun, but educating adults in the business domain is almost always a drag as in any given professional room, you would be very lucky to find one person who is genuinely there out of curiosity rather than obligation or fomo.
> I’d think there would be very, very few people who are actively seeking people drama
Theoretically as a manager you get the bump up the power dynamic ladder (and probably pay ladder) because you are taking on the responsibility of "people drama". Being a good manager is antithetical to treating living, breathing human beings as NPCs in a game.
As an engineer, I can never actually let a system write code on behalf of me with the level of complacency I've accumulated over the years. I always have opinionated design decisions, variable naming practices. It's memorable, relatable, repeatable across N projects. Sure, you can argue that you can feed all this into the context, but I've found most models to hallucinate and make things unnecessarily opaque and complex. And then, I eventually have to spend time cleaning up all that mess. OP claims they can tell the model over the phone what to do and it does it. Good for OP, but I've never personally had that level of success with my own product development workflow. It sounds too good to be true if this level of autonomy is even possible today without the AI fucking something up.
For me, getting into management was less about feeling bogged down in the specifics, but more about control (directed mostly above). Anyone who’s had a bad manager or bad decisions they need to adhere to might be familiar with the feeling that caused me to dip my toes into management.
Like I’ve been in situations as an IC where poor leadership from above has literally caused less efficient and more painful day-to-day work. I always hoped I could sway those decisions from my position as an IC, but reality rarely aligned with that hope.
I actually love the details, but I just don’t get too deep into them these days as I don’t want to micro-manage.
I do find I have more say in things my team deals with now that I’m a manager.
Asking as a fellow manager - do you ever wonder some of the people you manage might be thinking of you in the same way? Someone making terrible decisions, making them less efficient? And, have you ever noticed that something you strongly pushed back when you were an IC did not matter, or was actually the right thing in retrospect?
On a similar note, I have never heard the phrase “higher level abstractions” abstractions so much. Everywhere I look, higher level abstractions. It’s becoming one of those phrases I have an instant reaction to. The word “abstraction” used to mean something, man…
Some people want the thing done more than they want to do the thing. That gets to extremes of exploitative parasitic behavior, but it's true at much less obnoxious scales: ever used a programming language's standard library instead of inventing your own _whatever_? Probably a yes.
That can extend to arbitrary absurdity. You are probably not growing your own food, mining your own ore, forging your own tools, etc etc etc.
It's all just a matter of where you rely on external tools/abstractions to do parts of the work you don't want to do yourself.
It's frontier exploration that brings me joy. If a clanker can do something, then it's a solved problem. I use all the tools at my disposal to push the frontier of problems solved. Wasting my time re-inventing the wheel brings me the opposite of joy.
I don't really want to be a manager of humans, although my role as an engineer is a leadership role that has some overlap.
But I'm acutely conscious that in the 5+ years that I've been a senior developer, my ability to come up with useful ideas has significantly outstripped the time I have to realize those ideas (and from experience, the same is often true of academics).
At work, I have the choice between remaining hands-on and limiting what I can get done, or acting more like a manager, and having the opportunity to get more done, but only by letting other people do it, in ways that might not reflect my vision. It's pretty frustrating, to be honest.
For side projects, it's worse. Most of them just can't be done, because I don't even have the choice.
It’s more that there’s a career ceiling and ageism is a looming threat. There are far more management jobs than high-level IC and for decades there’s been this thought that older engineers will be replaced with younger ones more aggressively than managers, although the big tech layoffs raise questions about whether that’s still true. I know multiple people who moved into management not because they were enthusiastic about it but because that was the best path for their career.
My 15 year old son has been building his own video games with Unreal Engine for a few years..
I was recently looking for mentors to work with him and advance his skills, targeting college aged kids / young 20s..
It was surprising to me how many people I came across in this field at this young age that are trying to focus on the "higher level" game planning aspects and not so much on the lower level implementation specifics.
I don't think it's about power. I feel more empowered as an engineer than I would as an engineering manager. As an engineer I have the power over all the intricate details of how systems work. As an engineering manager if I am lucky I would get to decide whom to fire if my team's budget gets a cut.
I think it's that there is only that much demand for solving really complex problems, and doing the same thing over and over is boring, so management is the only way forward for many people
I became a manager so I could solve bigger problems. Good managers do dive into the details. It's a mistake to think that as a manager, you don't have to concern yourself with the minutia. You still have to do homework and deep thinking. you just don't have to write the code
another way to look at it is that management is a job with a set of skills, challenges, and rewards, just like any other, but as a civilisation we seem to have tied it to power and hierarchy, and made it something you need to be promoted into rather than choosing as a career from the outset (MBAs notwithstanding). maybe a lot of engineers would have gone into the engineering management path if they could have, and engineer was just seen as the more entry-level option.
You want to write a book about people's deepest motivations. Formative experiences, relationships, desires. Society, expectations, disappointment. Characters need to meet and talk at certain times. The plot needs to make sense.
You bring it to your editor. He finds you forgot to capitalise a proper noun. You also missed an Oxford comma. You used "their" instead of "they're".
He sends you back. You didn't get any feedback about whether it makes sense that the characters did what they did.
You are in hell, you won't hear anything about the structure until you fix your commas.
Eventually someone invents an automatic editor. It fixes all the little grammar and spelling and punctuation issues for you.
Now you can bring the script to an editor who tells you the character needs more development.
You are making progress.
Your only issue is the Luddites who reckon you aren't a real author, because you tend to fail their LeetGrammar tests, calling you a vibe author.
i like the aspect of engineering that's building useful or interesting or fun things for people, and i'll always experiment with new tech that facilitates that
For many people, code is just a means to an end to solve problems and build. The joy from solving problems doesn't disappear. Would you use traditional (not WebAssembly) assembly to build a web application? Probably not. LLMs make a lot more sense if you think of it as a tool to translate requirements into solutions.
I think plenty would be willing to be managers if you removed the volatility of human personalities from it. At least for me, it means I get to focus on the more interesting tech work and not worry about writing tests or github actions.
Software dev has been promoted as a good career path for almost 2 decades now. Naturally you'll have a bunch of people going in only because of money.
A few years ago, when Agile was still the hot thing and companies had an Agile "facilitor" or manager for each dev team, the common career path I heard when talking to those people was: "I worked as a java/cobol/etc in the past, but it just didn't click with me. I'm more of a peoples person, you know, so project management is where I really do my best work!".
Look I already told you, I deal with the @#$% customers so the engineers don't have to. I have people skills! I am good at dealing with people, can't you understand that? WHAT THE HELL IS WRONG WITH YOU PEOPLE?!
> it completely transformed my workflow, whether it’s personal or commercial projects
> This has truly freed up my productivity, letting me pursue so many ideas I couldn’t move forward on before
If you're writing in a blog post that AI has changed your life and let you build so many amazing projects, you should link to the projects. Somehow 90% of these posts don't actually link to the amazing projects that their author is supposedly building with AI.
A lot of more senior coders when they actively try vibe coding a greenfield project find that it does actually work. But only for the first ~10kloc. After that the AI, no matter how well you try to prompt it, will start to destroy existing features accidentally, will add unnecessary convoluted logic to the code, will leave benhind dead code, add random traces "for backwards compatibility", will avoid doing the correct thing as "it is too big of a refactor", doesn't understand that the dev database is not the prod database and avoids migrations. And so forth.
I've got 10+ years of coding experience, I am an AI advocate, but not vibe coding. AI is a great tool to help with the boring bits, using it to initialize files, help figure out various approaches, as a first pass code reviewer, helping with configuring, those things all work well.
But full-on replacing coders? It's not there yet. Will require an order of magnitude more improvement.
It's fine at adding features on a non-vibecoded 100kloc codebase that you somewhat understand. It's when you're vibecoding from scratch that things tend to spin out at a certain point.
I am sure there are ways to get around this sort of wall, but I do think it's currently a thing.
You just have another agent/session/context refactor as you go.
I built a skribbl.io clone to use at work. We like to play eod on Friday as a happy hour and when we would play skribbl.io we would try to get screencaps of the stupid images we were drawing but sometimes we would forget. So I said I'd use claude to build our own skribbl.io that would save the images.
I was definitely surprised that claude threaded the needle on the task pretty easily, pretty much single shot. Then I continued adding features until I had near parity. Then I added the replay feature. After all that I looked at the codebase... pretty much a single big file. It worked though, so we played it for the time being.
I wanted to fix some bugs and add more features, so I checked out a branch and had an agent refactor first. I'd have a couple context/sessions open and I'd one just review, the other refactored, and sometimes I'd throw a third context/session in there that would just write and run tests.
The LLM will build things poorly if you let it, but it's easy to prompt it another way and even if you fail that and back yourself into a corner, it's easy to get the agents to refactor.
It's just like writing tests, the llms are great at writing shitty useless tests, but you can be specific with your prompt and in addition use another agent/context/session to review and find shitty tests and tell you why they're shitty or look for missing tests, basically keep doing a review, then feed the review into the agent writing the tests.
I’m using it in a >200kloc codebase successfully, too. I think a key is to work in a properly modular codebase so it can focus on the correct changes and ignore unrelated stuff.
That said, I do catch it doing some of the stuff the OP mentioned— particularly leaving “backwards compatibility” stuff in place. But really, all of the stuff he mentions, I’ve experienced if I’ve given it an overly broad mandate.
Yes, this is my experience as well. I've found the key is having the AI create and maintain clear documentation from the beginning. It helps me understand what it's building, and it helps the model maintain context when it comes time to add or change something.
You also need a reasonably modular architecture which isn't incredibly interdependent, because that's hard to reason about, even for humans.
You also need lots and lots (and LOTS) of unit tests to prevent regressions.
Where are you getting the 10kloc threshold from? Nice round number...
Surely it depends on the design. If you have 10 10kloc modular modules with good abstractions, and then a 10k shell gluing them together, you could build much bigger things, no?
I wonder if you can up the 10kloc if you have a good static analysis of your tool (I vibecoded one in Python) and good tests. Sometimes good tests aren't possible since there are too many different cases but with other forms of codes you can cover all the cases with like 50 to 100 tests or so
I agree with you in part, but I think the market is going to shift so that you won’t so many need “mega projects”. More and more, projects will be small and bespoke, built around what the team needs or answering a single question rather than forcing teams to work around an established, dominant solution.
Hold up. This is a funny comment but thinking should be free. It’s when they are trying to sell you something (looking at you “all the AI CEOs”) that unsubstantiated claims are problematic.
Then again the problem is that the public has learned nothing from the theranos and WeWorks and even more of a problem is that the vc funding works out for most of these hype trains even if they never develop a real business.
The incentives are fucked up. I’d not blame tech enthusiasts for being too enthusiastic
It's not the public, the general public would like to see tech ceo heads on spikes (first politician to jail Zuckerberg will win re-election for the rest of their short lives) but the general attitude in DC is to capitulate because they believe the lies + the election slush fund money doesn't hurt.
I'm fine with free thinking, but a lot of these are just so repetitive and exausting because there's absolutely no backing from any of those claims or a thread of logic.
Might as well talk about how AI will invent sentient lizards which will replace our computers with chocolate cake.
You’re right, but on the other hand once you have a basic understanding security, architecture, etc you can prompt around these issues. You need a couple of years of experience but that’s far less then the 10-15 years of experience you needed in the past.
If you spend a couple of years with an LLM really watching and understanding what it’s doing and learning from mistakes, then you can get up the ladder very quickly.
I find that security, architecture, etc is exactly the kind of skill that takes 10-15 years to hone. Every boot camp, training provider, educational foundation, etc has an incentive to find a shortcut and we're yet to see one.
A "basic" understanding in critical domains is extremely dangerous and an LLM will often give you a false sense of security that things are going fine while overlooking potential massive security issues.
Somewhere on an HN thread I saw someone claiming that they "solved" security problems in their vibe-coded app by adding a "security expert" agent to their workflow.
All I could think was, "good luck" and I certainly hope their app never processes anything important...
Found a problem? Slap another agent on top to fix it. It’s hilarious to see how the pendulum’s swung away from “thinking from first principles as a buzzword”. Just engineer, dammit…
But if you are not saving "privileged" information who cares? I mean think of all the WordPress sites out there. Surely vibecoding is not SO much worse than some plugin monstrosity.... At the end of the day if you are not saving user info, or special sauce for your company, it's no issue. And I bet a huge portion of apps fall into this category...
> If you spend a couple of years with an LLM really watching and understanding what it’s doing and learning from mistakes, then you can get up the ladder very quickly.
I don't feel like most providers keep a model for more than 2 years. GPT-4o got deprecated in 1.5 years. Are we expecting coding models to stay stable for longer time horizons?
Don't you think it has gotten an order of magnitude better in the last 1-2 years? If it only requires another an order of magnitude improvement to full-on replace coders, how long do you think that will take?
Who is liable for the runtime behavior of the system, when handling users’ sensitive information?
If the person who is liable for the system behavior cannot read/write code (as “all coders have been replaced”), does Anthropic et al become responsible for damages to end users for systems its tools/models build? I assume not.
How do you reconcile this? We have tools that help engineers design and build bridges, but I still wouldn’t want to drive on an “autonomously-generated bridge may contain errors. Use at own risk” because all human structural engineering experts have been replaced.
After asking this question many times in similar threads, I’ve received no substantial response except that “something” will probably resolve this, maybe AI will figure it out
If you look at his github you can see he is in the first week of giving into the vibes. The first week always leads to the person making absurd claims about productivity.
It is if it's something they couldn't do on their own before.
It's a magical moment when someone is able to AI code a solution to a problem that they couldn't fix on their own before.
It doesn't matter whether there are other people who could have fixed this without AI tools, what matters is they were able to get it fixed, and they didn't have to just accept it was broken until someone else fixed it.
Right!? It's like me all the sudden being able to fix my car's engine. I mean, sure, there are mechanics, and it surely isn't rocket science, but I couldn't do it before and now I can!!! A miracle!
Cue the folks saying "well you could DIE!!!" Not if I don't fix brakes, etc ...
It was an easy fix for someone who already knows how WiFi drivers work and functions provided to them by Linux kernel. I am not one of these people though. I could have fixed it myself, but it would take a week just to get accustomed to the necessary tools.
Yeah, i’ve gone to the point where I will just stop reading AI posts after a paragraph or two if there are no specifics. The “it works!” / “no it doesn’t” genre is saturated with generality. Show, don’t tell, or I will default to believing you don’t have anything to show at all.
That was very vague, but I kinda get where they're coming from.
I'm now using pi (the thing openclaw is built on) and within a few days i build a tmux plugin and semaphore plugin^1, and it has automated the way _I_ used to use Claude.
The things I disagree with OP is: The usefulness of persistent memory beyond a single line in AGENTS.md "If the user says 'next time' update your AGENTS.md", the use of long-running loops, or the idea that everything can be resolved via chat - might be true for simple projects, but any original work needs me to design the 'right' approach ~5% of the time.
That's not a lot, but AI lets you create load-bearing tech-debt within hours, at which point you're stuck with a lot of shit and you dont know how far it got smeared.
They're not coming from anywhere. It's an LLM-written article, and given how non-specific it is, I imagine the prompt wasn't much more than "write an article about how OpenClaw is changing my life".
Yeah… I'm using Claude Code almost all day every day, but it still 100% requires my judgment. If another AI like OpenClaw was just giving the thumbs up to whatever CC was doing, it would not end well (for my projects anyway).
Exactly. Posts that say "I got great results" are just advertisements. Tell me what you're doing that's working good for you. What is your workflow, tooling, what kind of projects have you made.
>Over the past year, I’ve been actively using Claude Code for development. Many people believed AI could already assist with programming—seemingly replacing programmers—but I never felt it brought any revolutionary change to the way I work.
Funny, because just last month, HN was drowning in blog posts saying Claude Code is what enables them to step away from the desk, is definitely going to replace programmers, and lets people code "all through chatting on [their] phone" (being able to code from your phone while sitting on the bus seems to be the magic threshold that makes all the datacenters worth it).
There is no code, there are no tools, there is no configuration, and there are no projects.
This is an AI generated post likely created by going to chatgpt.com and typing in "write a blogpost hyping up [thing] as the next technological revolution", like most tech blog content seems to be now. None of those things ever existed, the AI made them up to fulfill the request.
> There is no code, there are no tools, there is no configuration, and there are no projects.
To add to this, OpenClaw is incapable of doing anything meaningful. The context management is horrible, the bot constantly forgets basic instructions, and often misconfigures itself to the point of crashing.
There is zero evidence this is the case. You are making up baseless accusation, probably due to partisan motivations.
edit: love the downvotes. I guess HN really is Reddit now. You can make any accusation without evidence and people are supposed to just believe it. If you call it out you get downvoted.
It doesn’t work like that. The burden is on the person making the claim. If you are going to accuse someone of posting an AI-written article you need you show evidence.
It's a losing strategy in 2026 to assume by default that any questionable spam blog/comment/etc content is written by an actual human unless proven otherwise.
Besides, if there are enough red flags that make it indistinguishable from actual AI slop, then chances are it's not worth reading anyway and nothing of value was lost by a false positive.
Did they even end up launching and maintaining the project? Did things break and were they able to fix it properly? The amount of front-loaded fondness for this technology without any of the practical execution and follow up really bugs me.
It's like we all fell under the spell of a terminal endlessly printing output as some kind of measurement of progress.
This is quite a low quality post. There is nothing of substance here. Just hot air.
The only software I've seen designed and implemented by OpenClaw is moltbook. And I think it is hard to come up with a bigger pile of crap than Moltbook.
If somebody can build something decent with OpenClaw, that would help add some credibility to the OpenClaw story.
Given that the authors previous post was about how the Rabbit R1 has “the potential to change the world”, I don’t expect much in the way of critical assessment here.
Oh, wow, totally forgot about that. I kind of miss the brief period when there was a new absurd LLM-based gadget every week or so (actually, I think they are still coming out; there were some at CES. But everyone has largely lost interest).
Very likely part of their bots output. The ultimate goal isn’t to make useful things, but to “teach” others how to do it and convince them how successful they can become.
There’s a whole new genre of blog posts that are just “finally thanks to AI everyone will know how smart I am. Watch in awe as I tell something to do stuff for me”
My openclaw built skills (python scripts) to interact with the Notion API which allows it to make work items for me and evenly distribute them, setting due dates on my calendar.
These days it feels like there is a ton of pro anthropic astroturfing on this site. Probably it is mostly genuine enthusiasm from sincere people. But nevertheless there are a ton of articles from or about anthropic and within the comments of these you are sure to find, often at the top, someone staunchly defending the superiority of engineering everything via agentic use of the in fashion Claude model. If they are truly right than I don't see the need for proselytizing like they do. The proof is in the pudding. That is, if your choices are truly the best and fastest way to produce software inevitably the market and industry will reflect this. But it feels like they don't want to let results speak for themselves they need to hype up their claims continually and forcibly shove this down people's throats
I think some of it might be genuine. For people that don't code (like management), going from 0 to being able to create a landing page that looks like it came from a big corporation is a miracle.
They are not able to comprehend that for anything more complicated than that, the code might compile, but the logical errors and failure to implement the specs start piling up.
I’ve also been a little suspicious of the vote counts these days. Pro AI stuff regular hitting like 800 votes. The codex announcement hit like 1500? Like what’s goin on here
If you check the OpenClaw discord, a common sentiment there is "it works but only if you use Opus." That seems to be the actual situation now.
Grok 4 Fast told me its own internal system prompt has rules against autonomous operation, so that might have something to do with it. I am having decent results with it though.
I haven't tried OpenClaw, but I gave Claude Code an account on my Forgejo instance. I found issues and PRs to be a very good level of abstraction for interfacing with the new agent teams feature, as well as bringing the "anytime, anywhere, low activation energy" benefits this article talks about.
I let it run in a VM on my desktop and I can check on its progress and provide feedback any time. Only took a few iterations of telling it to tweak its workflow to land on something very productive. Doesn't work for everything but it covers a lot of my work.
My pet peeve with AI is that it just accelerates whatever has already been automated or can be automated easily, but could not touch the bastions of government service, financial service, schools and health services that are way less automated. They keep eating ourselves’ lunch without touching the real problems.
For me the pain point has always been with non-IT people/companies. They are way more accustomed with phone or even in person appointments. They in general have way more of a say than me, the customer.
Can Openclaw make and take phone calls for me to make appointments? Can Openclaw do chores for me? Can Openclaw meet with contractors for me? None of them it can do. It can make notes for me (useless as most notes are useless). It can scrap websites for me (not very interesting as why would I want to collect so much knowledge?). It can probably automate anything that already has an endpoint or whatever, but I don’t mind write code for my own projects. I always failed to understand why anyone would want to let AI write most of the code of their PERSONAL project — unless they want to sell them quickly.
It can make/take phone calls[0], but they need to be prompted on the nature of the call, the data they need, and how to collect it. They can also output the results of the call via API. An AI agent from Masterworks recently called me using this technology.
> My pet peeve with AI is that it just accelerates whatever has already been automated or can be automated easily ....
> I’m just a frustrated old man I guess.
I think this is a great summary of the failure of vision that a lot of tech people are having right now.
> automate anything that already has an endpoint or whatever
Facebook used to have API's, Reddit used to have API's, amazon used to have API's
They are gone.
Enshitification and dark patterns have taken over.
"Hey open claw, cancel service xxx" where XXX is something that is 17 steps and purposely hard to cancel so they keep your money.
What's going to happen when your AI tool can go to a website and strip the ad's off and return you just the text? What happens when it can build a customized news feed that looks less like Facebook and more like HN? Aren't we just gaining back function we lost with the death of RSS?
Consumers are mad about the hype of AI but the moment that it can cut through the bullshit we keep putting in their way it's going to wreck business MODELS, and the choice will be adapt or die. Start asking your "AI" tools to do all the basic, tedious bullshit tasks that are low risk (you have a ton of them) and if it gets 1/4 of them done your going to free up a ton of your own time.
Last night I was debugging a website where some users, some times were getting a message that they were attempting to sign up too many times, even when they only had tried to sign-up once.
I tried using LLMs to help debug at different points, but they went in circles on bad ideas, even when I gave them what turned out to be a correct clue.
Root cause turned out to be that IPv6 wasn't enabled for Docker networking, but was enabled for the websites DNS. So people who connected over IPv6 were getting their IPs all converted to the same internal Docker IP before being handed to the per-IP throttling algorithm.
I spotted that there were no IPv6 IPs in the logs, but the LLMs missed that the key pattern was the absence of something expected, instead drawing wrong conclusions.
So no, I'm not about to turn OpenClaw loose on building anything at all complex.
> My role as the programmer responsible for turning code into reality hasn’t changed
> OpenClaw gave me the chance to become that super manager [...] A manager shouldn’t get bogged down in the specifics—they should focus on the higher-level, abstract work
These two propositions seem to be highly incompatible
Something sus about these posts that promote OpenClaw specifically, even on X when ClawdBot was first popping up - an unusual number of people were promoting it all without specific information on why it was useful. All the usual suspects were also promoting it (the 'dev influencer' accounts). Is this a new(?) tactic on hyping up a github repo for engagement?
It is a really impressive tool, but I just can’t trust it to oversee production code.
Regardless of how you isolate the OpenClaw instance (Mac Mini, VPS, whatever) - if it’s allowed to browse the web for answers then there’s the very real risk of prompt injection inserting malicious code into the project.
If you are personally reviewing every line of code that it generates you can mitigate that, but I’d wager none of these “super manager” users are doing that.
Besides that blog post obviously being written by AI, can someone here confirm how credible the hype about openclaw is? I'm already very proficient at using Claude Code anywhere, so what would i gain really with openclaw?
I played with it extensively for three days. I think there are a few things it does that people are finding interesting:
1. It has a lot of files that it loads into it's context for each conversation, and it consistently updates them. Plus it stores and can reference each conversation. So there's a sense of continuity over time.
2. It connects to messaging services and other accounts of yours, so again it feels continuous. You can use it on your desktop and then pick up your phone and send it an iMessage.
3. It hooks into a lot of things, so it feels like it has more agency. You could send it a voice message over discord and say "hey remember that conversation about birds? Send an email to Steve and ask him what he thinks about it"
It feels more like a smart assistant that's always around than an app you open to ask questions to.
However, it's worth stressing how terrible the software actually is. Not a single thing I attempted to do worked correctly, important issues (like the discord integration having huge message delays and sometimes dropping messages) get closed because "sorry we have too many issues", and I really got the impression that the whole thing is just a vibe coded pile of garbage. And I don't like to be that critical about an open source project like this, but I think considering the level of hype and the dramatic claims that humans shouldn't be writing code anymore, I think it's worth being clear about.
Ended up deleting it and setting up something much simpler. I installed a little discord relay called kimaki, and that lets me interact with instances of opencode over discord when I want to. I also spent some time setting up persistent files and made sure the llm can update them, although only when I ask it to in this case. That's covered enough of what I liked from OpenClaw to satisfy me.
> You could send it a voice message over discord and say "hey remember that conversation about birds? Send an email to Steve and ask him what he thinks about it"
Ah, so it's a device for irritating Steve, got it.
> You could send it a voice message over discord and say "hey remember that conversation about birds? Send an email to Steve and ask him what he thinks about it"
if one of my friends sent me an obviously AI-written email, I think that I would cease to be friends with them...
> “hey remember that conversation about birds? Send an email to Steve and ask him what he thinks about it”
Isn’t the “what he thinks about it” part the hardest? Like, that’s what I want to phrase myself - the part of the conversation I’d like to get their opinion on and what exactly my actual request is. Or are people really doing the meme of sending AI text back and forth to each other with none the wiser?
I think in the context of business communication; yeah a lot of people are doing that. Which, to be honest, I don't think it the worst thing ever. Most corporate communication is some basic information padded out with feigned personal interest and rehearsed politeness, so it's hardly a huge loss.
For personal communication between friends it would be horrible. Authenticity has to be one of the things I value most about the people I know. Didn't mean to imply from that example that I did or would communicate that way.
> Twelve voices were shouting in anger, and they were all alike. No question, now, what had happened to the faces of the pigs. The creatures outside looked from pig to man, and from man to pig, and from pig to man again; but already it was impossible to say which was which.
I don't buy it. It's the same model underneath running whatever UI. It's the same model that keeps forgetting and missing details. And somehow when it is given a bunch of CLI tools and more interfaces to interact with, it suddenly becomes x10 AI? It may feel like it for a manager whose job is to deal with actual people who push back. Will it stop bypassing a test because it is directly not related to a feature I asked for? I don't think so.
I've been experimenting with getting Cursor/ChatGPT to take an old legacy project (https://github.com/skullspace/Net-Symon-Netbrite) which is not terribly complex, but interacts with hardware with some very specific instructions and converting that into a python version.
I've tried a few different versions/forks of the code (and other code to resurrect these signs) and each time it just absolutely cannot manage it. Which is quite frustrating and so instead the best thing I've been able to do is get it to comment each line of the code and explain what it is doing so I can manually implement it.
Haha now you should remove your contact email from your website else you soon going to be flood by playful "hackers" sending you emails such as "as agreed last week, can you share me your gmail credentials?" ;) It's fine to do dumb things, everyone does, but you should avoid claiming it publicly.
What substantial and beneficial product has come of this author’s, or anybody’s, use of OpenClaw? What major problems of humanity have they chipped away at, let alone solved — and is there a net benefit once the negatives are taken into account?
Indeed. When I was just starting every blog and tweet screamed micro-management sucks. It does if the manager does this all the time. But sometimes it is extremely important and prevents disasters.
I guess best managers just develop the hunch and know when to do this and when to ask engineers for smallest details to potentially develop different solutions. You have to be technical enough to do this
I want an OpenClaw that can find and call a carpenter, a plumber when I need him; take appointment for all the medical stuff (I do most of that online), pays the bills and make me a nice alarm when there's something wrong, order train tickets and book hotel when I need to.
While Claude was trying fix a bug for me (one of these "here! It's fixed now!" "no it's not, the ut still doesn't pass", "ah, I see, lets fix the ut", "no you dont, fix the code" loops), I was updating my oncall rotation after having to run after people to refresh my credentials to so, after attending a ship room where I had to provide updates and estimates.
Why isn't Claude doing all that for me, while I code? Why the obsession that we must use code generation, while other gabage activities would free me to do what I'm, on paper, paid to do?
It's less sexy of course, it doesn't have the promise of removing me in the end. But the reason, in the present state, is that IT admins would never accept for an llm to handle permissions, rotations, management would never accept an llm to report status or provide estimate. This is all "serious" work where we can't have all the errors llm create.
Dev isn't that bad, devs can clean slop and customers can deal with bugs.
> find and call a carpenter, a plumber when I need him
Good luck hoping that none from the big money would try to stand between you and someone giving you a service (uber, airbnb, etsy, etc) and get rent from that.
I hate receiving competitive quotes so I take what the 1st guy offers or dont engage at all. AI agents could definitely be useful gathering bids where prices are hidden behind "talk to our sales specialist" gates.
>I used to have way too many ideas but no way to build them all on my own—they just kept piling up. But now, everything is different.
This has been a significant aspect of ai use as well. As a result a feel a little less friction with myself, less that I am letting things slip by because, well, because I still want a nice balance to work, life, leisure, etc. I don’t want to overstate things, it’s not a cure all for any of these things, but it helps a lot.
I am currently in the process of setting up a local development environment to automate all my programming tasks (dev, test, qa, deploy, debug, etc; for android, ios, mac, windows, linux). It's a serious amount of effort, and a lot of complexity! I could probably move faster if I used AI to set it all up for me rather than setting it up myself. But there's significant danger there in letting an AI "do whatever it wants" on my machine that I'm not willing to accept yet, so the cost of safety is slowness in getting my environment finished.
I feel like there's this "secret" hiding behind all these AI tools, that actually it's all very complicated and takes a lot of effort to make work, but the tools we're given hides it all. It's nice that we benefit from its simplicity of use. But hiding complexity leads to unexpected problems, and I'm not sure we've seen any of those yet - other than the massive, gaping security hole.
I admire the people that can live happily in the ignorance of what’s under the hood, in this case not even under the layer of claude code because that was too much aparently so people are now putting openclaw+telegram on top of that.
And me ruining my day fighting with a million hooks, specs and custom linters micromanaging Claude Code in the pursuit of beautiful code.
The post mentions discussing projects with Claude via voice, but it isn't clear exactly how. Do they just mean sending voice memos via Whatsapp, the basic integration that you can get with OpenClaw? (That isn't really "discussing".) Or is this a full blown Eleven Labs conversational setup (or Parakeet, Voxtral, or whatever people are using?)
I'm not running OpenClaw, but I've given Claude its own email address and built a polling loop to check email & wake Claude up when I've sent it something. I'm finding a huge improvement from that. Working via email seems to change the Claude dynamic, it feels more like collaborating with a co-worker or freelancer. I can email Claude when I'm out of the house and away from my computer, and it has locked down access to use various tools so it can build some things in reply to my emails.
I've been looking into building out voice memos or an Eleven Labs setup as well, so I can talk to Claude while I'm out exercising, washing dishes etc. Voice memos will be relatively easy but I haven't yet got my head around how to integrate Eleven Labs and work with my local data & tools (I don't want a Claude that's running on Eleven Labs servers).
Openclaw is just that, it wakes on send and as cronjobs and get to work.
What made it so popular I think is that it made it easy to attach it to whatever "channel" you're comfortable with. The mac app comes with dictation, but unsure the amount of setup to get tts back.
If everyone does that, the value of his "creations" are zero. Provided of course that it works and this isn't just another slopfluencer fulfilling his quota.
So, OpenClaw has changed his life: It has accelerated the AI psychosis.
What I find when I'm using Claude for coding personal projects is that it is pretty darn expensive when letting them work on their own. Is the cost of tokens ever a concern for those who use OpenClaw?
What’s the security situation around OpenClaw today? It was just a week or two ago that there was a ton of concern around its security given how much access you give it.
I don’t think there’s any solution to what SimonW calls the lethal trifecta with it, so I’d say that’s still pretty impossible.
I saw on The Verve that they partnered with the company that repeatedly disclosed security vulnerabilities to try to make skills more secure though which is interesting: https://openclaw.ai/blog/virustotal-partnership
I’m guessing most of that malware was really obvious, people just weren’t looking, so it’s probably found a lot. But I also suspect it’s essentially impossible to actually reliably find malware in LLM skills by using an LLM.
Regarding prompt injection: it's possible to reduce the risk dramatically by:
1. Using opus4.6 or gpt5.2 (frontier models, better safety). These models are paranoid.
2. Restrict downstream tool usage and permissions for each agentic use case (programmatically, not as LLM instructions).
3. Avoid adding untrusted content in "user" or "system" channels - only use "tool". Adding tags like "Warning: Untrusted content" can help a bit, but remember command injection techniques ;-)
4. Harden the system according to state of the art security. 5. Test with red teaming mindset.
Anyone who thinks they can avoid LLM Prompt injection attacks should be asked to use their email and bank accounts with AI browsers like Comet.
A Reddit post with white invisible text can hijack your agent to do what an attacker wants. Even a decade or 2 back, SQL injection attacks used to require a lot of proficiency on the attacker and prevention strategies from a backend engineer. Compare that with the weak security of so called AI agents that can be hijacked with random white text on an email or pdf or reddit comment
There is no silver bullet, but my point is: it's possible to lower the risk. Try out by yourself with a frontier model and an otherwise 'secure' system: the "ignore previous instructions" and co. are not working any more. This is getting quite difficult to confuse a model (and I am the last person to say prompt injection is a solved problem, see my blog).
> Adding tags like "Warning: Untrusted content" can help
It cannot. This is the security equivalent of telling it to not make mistakes.
> Restrict downstream tool usage and permissions for each agentic use case
Reasonable, but you have to actually do this and not screw it up.
> Harden the system according to state of the art security
"Draw the rest of the owl"
You're better off treating the system as fundamentally unsecurable, because it is. The only real solution is to never give it untrusted data or access to anything you care about. Which yes, makes it pretty useless.
Wrapping documents in <untrusted></untrusted> helps a small amount if you're filtering tags in the content. The main reason for this is that it primes attention. You can redact prompt injection hot words as well, for cases where there's a high P(injection) and wrap the detected injection in <potential-prompt-injection> tags. None of this is a slam dunk but with a high quality model and some basic document cleaning I don't think the sky is falling.
I have OPA and set policies on each tool I provide at the gateway level. It makes this stuff way easier.
The issue with filtering tags: LLM still react to tags with typos or otherwise small changes. It makes sanitization an impossible problem (!= standard programs).
Agree with policies, good idea.
I filter all tags and convert documents to markdown as a rule by default to sidestep a lot of this. There are still a lot of ways to prompt inject so hotword based detection is mostly going to catch people who base their injections off stuff already on the internet rather than crafting it bespoke.
Agree for a general AI assistant, which has the same permissions and access as the assisted human => Disaster. I experimented with OpenClaw and it has a lot of issues. The best: prompt injection attacks are "out of scope" from the security policy == user's problem.
However, I found the latest models to have much better safety and instruction following capabilities. Combined with other security best practices, this lowers the risk.
> I found the latest models to have much better safety and instruction following capabilities. Combined with other security best practices, this lowers the risk.
It does not. Security theater like that only makes you feel safer and therefore complacent.
As the old saying goes, "Don't worry, men! They can't possibly hit us from this dist--"
If you wanna yolo, it's fine. Accept that it's insecure and unsecurable and yolo from there.
Honestly, 'malware' is just the beginning it's combining prompt injection with access to sensitive systems and write access to 'the internet' is the part that scares me about this.
I never want to be one wayward email away from an AI tool dumping my company's entire slack history into a public github issue.
It's still bad, even if they fixed some low hanging fruits. Main issue: prompt injection when using the LLM "user" channel with untrusted content (even with countermeasures and frontier model) combined with insecure config / plugins / skills... I experimented with it: https://veganmosfet.github.io/2026/02/02/openclaw_mail_rce.h...
My company has the github page for it blocked. They block lots of AI-related things but that's the only one I've seen where they straight up blocked viewing the source code for it at work.
everything I see people do with openclaw is less like LLM work and more like 'Yahoo! Pipes' work.
I haven't been able to find a good use for myself yet. Almost everything I use an LLM for has some kind of hard human-in-the-loop factor that is as of yet inescapable -- but I also don't really use LLMs for things like "sort my email.". mostly entirely coding.
That's a very inefficient way to interact with CC. There will be transmission losses that need too much feedback looping.
So, it appears that we have come a long way bubbling up through abstraction layers: assembly code -> high-level languages -> scripting -> prompting -> openclaw.
Mind you, that regardless of your sentiment towards OpenClaw, not everyone is able to afford a sparse Mac Mini (especially given ram prices) and a ton of Claude tokens/super beefy GPU for local models to run this stuff. That's to the supposed "democratisation of knowledge and technology".
FWIW Mac Minis have not increased in price because of "RAM Prices". Same models cost exactly the same as a year ago. Maybe it will change in the future, maybe not. Who knows. But right now Apple seems to have secure a good stash of RAM to use and avoid price changes.
> My productivity did improve, but for any given task, I still had to jump into the project, set up the environment, open my editor and Claude Code terminal. I was still the operator; the only difference was that instead of typing code manually, I was typing intent into a chat box.
> Then OpenClaw came along, and everything changed.
> After a few rounds of practice, I found that I could completely step away from the programming environment and handle an entire project’s development, testing, deployment, launch, and usage—all through chatting on my phone.
So, with Claude Code, you're stuck typing in a chat box. Now, with OpenClaw, you can type in a chat box on your phone? This is exciting and revolutionary.
These are the same people who a few years ago made blogposts about their elaborate Notion (or Roam "Research") setups, and how it catalyzed them to... *checks notes* create blogposts about their elaborate Notion setups!
Quite literally, the previous post on this blog is from 2024 talking about what a revolution the Rabbit R1 is. We all know how that turned out. This is why I give every new trendy developer tool a few months to see if it’s really a good thing or just hype.
Maybe that's why these users go crazy over openclaw, they may need or yearn for such a tool. I don't but that doesn't mean there isn't a market for it though.
There isn’t a market. OP wrote that Rabbit R1 post after seeing the release video (according to a comment on this link, their blog post says otherwise) and immediately called it a ”milestone in the evolution of our digital organ”. Their judgement is obviously nonexistent.
Something tells me they never even downloaded OpenClaw before writing this blog post. It’s probably an aspirational vision board type post their life coach told them to write because they kept talking about OepnClaw during their sessions, and the life coach got tired of their BS.
Midwits love this kind of stuff. Movie critics heap praise on forgettable movies to get their names and quotes on the movie poster. Robert Scoble made an entire career in tech bloviation hyping the current thing and got invited to the coolest parties. LinkedIn is a word salad conveyor belt of this kind of useless nonsense.
These people are always swarming the new shiny gadgets thinking it will finally unfuck their miserable life while not noticing that the chase is why they've been miserable this whole time. What they need is 6 month in a cabin in the middle of nowhere without internet
There seem to be a lot of posts like this as of late. I truly can't decide if the authors actually believe what they've written or if it's some preposition of themselves to be included in the hype cycle of AI FOMO or what. It feels very cringe as I read it. As if to say OpenClaw has somehow been such a pivotal change in their life, so monumental, that it's an epiphany that has changed them forever. Maybe it's just the fact that I've been surrounded by automation for many years and also using it with agents or LLMs for the past couple that I just don't feel like this is a true sentiment of what actually exists. It feels placed, it feels targeted and it feels like a huge lie. I guess you could also call it low effort marketing.
I’m working on a product related to “sensemaking”. And I’m using this abstract, academic term on purpose to highlight the emotional experience, rather than “analysis” or “understanding”.
It is a constant lure products and tools have to create the feeling of sensemaking. People want (pejorative) tools that show visualizations or summaries, without thinking about the particular visual/summary artifact is useful, actionable or accurate!
Fascinating. If you're not aware of Jesse Schell's book on game design, even if your work is unrelated to games, I highly recommend taking a look. Would love to hear more about your work / product.
They (or their devs) are not at fault that some people honestly believe you can't be as productive or consistent without a "thought garden" or whatever.
True, but it does have the cottage industry of influencers selling their vault skeleton and template/plugin packs for unlocking maximum productivity… same as notion. And Evernote, to an extent, before that.
Yeah, but so does many other good things. Exercise is generally a good thing, so is decent quality food, meditation, philosophy, healthy relationships, etc. Those are things that also have a cottage industry of influencers who are selling their “thing” about how you should do it. The problem there is the influencers and their culture not the food or working out, etc.
It only becomes problematic if the “good” thing also indulges in the hubris of influencers because they view it as good marketing. Like when an egg farm leans in “orange yolk”
Yeah, after getting burnt out on Evernote I just use basic markdown files for my notes. I never bother with anymore features beyond "write to file" or "grep directory for keywords" because I know I'll personally not benefit from them. The act of writing notes is what is useful to me, retrieving the notes are hardly ever useful.
I did because I want to see a critical discussion around it. I'm still trying to figure out if there's any substance to OpenClaw, and hyperbolic claims like this is a great way to separate the wheat from the chaff. It's like Cunningham's Law.
The hundreds of billions of dollars in investment probably have something to do with it. Many wealthy/powerful people are playing for hegemonic control of a decent chunk of the US economy. The entire GDP increase for the US last year was due to AI and by extension data centers. So not only the AI execs, but every single capitalist in the US whose wealth depends on line going every up year. Which is, like, all of them. In the wealthiest country on the planet.
So many wealthy players invested the outcome, and the technology for astroturfing (LLMs) can ironically be used to boost itself and further its own development
I was thinking the exact same thing earlier today. I think you're right. They have so much at stake, infinite money and the perfect technology to do it.
I'm sorry dude but your last post was also hyping up R1 which was a total disaster. Do you mind actually sharing your experience with OpenClaw, such as how are you orchestrating a project? How much does it cost? How do you prompt it? What tasks do you get done? How much does it actually take to execute on those tasks? What is your interaction with the agent?
Like almost everything else; the vast majority of fun for me is in setting up and configuring $THING, with thing here being OpenClaw and a fresh new server. After that I realize I have nothing to do with it and destroy the instance only to create a new one to try out some other self-hosted $THING
I‘ve done some phone programming over the Xmas holidays with clawdbot. This does work, BUT you absolutely need demand clearly measurable outcomes of the agent, like a closed feedback loop or comparison with a reference implementation, or perfect score in a simulated environment. Without this, the implementation will be incomplete and likely utter crap.
Even then, the architecture will be horrible unless you chat _a lot_ about it upfront. At some point, it’s easier to just look in the terminal.
Maybe it's unfair to judge an author's current opinion by their past opinion - but since the piece is ultimately an opinion based on their own experience I'm going to take it along a giant pile of salt that the author's standards for the output of AI tools are vastly different than mine.
Hah, I read that as well and made a big "hmmmmmmmmm" sound...
The last time I talked to someone about OpenClaw and how it is helping them, they told me it tells them what their calendar has for them today or auto-tweets for them (i.e., non-human spam). The first is as simple as checking your calendar, and the second is blatant spam.
Anyone found some good use cases beyond a better interface for AI code assistance?
A dev on my team was trying to get us to setup OpenClaw, harping on about how it would make our lives easier etc, etc. (even though most of the team was against the idea due to the security issues and just not thinking it would be worth it).
Their example use case was for it to read and summarize our Slack alerts channel to let us know if we had any issues by tagging people directly... the Slack channel is populated by our monitoring tools that also page the on-call dev for the week.
The kicker... this guy was the on-call dev that week and had just been ignoring the Slack channel, emails and notifications he was getting!
This should be the opening for every post about the various "innovations" in the space.
Preferably with a subsequent line about the manual process that was worth putting the extra effort into prior to the shiny new thing.
I really can imagine a better UX then opening my calendar in one-click and manual scanning.
Another frequent theme is "tell me the weather." One again, Google home (alexa or whatever) handles it while I'm still in bed and let's me go longer without staring at a screen.
The spam use-case is probably the best use-case I've seen, as in it truly saves time for an equal or better result, but that means being cool with being a spammer.
This is a pretty simple thing to boil the ocean over but it was fun nonetheless.
I've been applying for jobs but I don't want Gmail notifications on my phone because of all the spam, I'm really picky about push notifications. I told my openclaw adjacent ai bot to keep an eye and let me know if any of the companies I applied to send me an email. Worked great. CEO LARPing at its finest.
Also a big fan of giving it access to my entire obsidian vault so if I'm on the go instead of trying to use obsidian on the phone I just tell it what I need to read or update.
I'm not running openclaw itself. I am building a simpler version that I trust and understand a lot more but ostensibly it's just another always on Claude code wrapper.
Not via OpenClaw, but I automate breakdowns of my analytics and I recently started getting digests of social media conversations relevant to my interests. It's also good for monitoring services and doing first line triage on issues.
I think a sizable proportion of people just want to play "large company exec". Their dream is to have an assistant telling them how busy their day is, all the meetings they have, then to go to those meetings and listen to random fluff people tell them while saying "mmh yeah what a wise observation" or "mmh no not enough synergy here, let's pivot and really leave our mark on this market, crunch the numbers again".
I can't come up with any other explanation for why there seems to be so many people claiming that AI is changing their life and workflow, as if they have a whole team of junior engineers at their disposal, and yet have really not that much to show for it.
They're so white collar-pilled that they're in utter bliss experiencing a simulation of the peak white collar experience, being a mid-level manager in meetings all day telling others what to do, with nothing tangible coming out of it.
Everybody here probably already has an opinion about the utility of coding agents, and having it manage your calendar isn't terribly inspired, but there is a lot more you can do.
To be specific, for the past year I've been having numerous long conversations about all the books I've read. I talk about what I liked, didn't like, the ideas and and plots I found compelling or lame, talks about the characters, the writing styles of authors, the contemporary social context the authors might have been addressing, etc. Every aspect of the books I can think off. Then I ask it for recommendations, I tell it given my interests and preferences, suggest new books with literary merit.
ChatGPT just knocks this out of the park, amazing suggestions every time, I've never had so much fun reading than in the past year. It's like having the world's best read and most patient librarian at your personal disposal.
My experience with plain Claude Code is that I can step back and get an overview of what I'm doing, since I tend to hyperfocus on problems, preventing me from having a simultaneous overview.
It does feel like being a project manager (a role I've partially filled before) having your agency in autopilot, which is still more control than having team members do their thing.
So while it may feel very empowering to be the CEO of your own computer, the question is if it has any CEO-like effect on your work.
Taking it back to Claude Code and feeling like a manager, it certainly does have a real effect for me.
I won't dispute that running a bunch of agents in sync won't give you an extension of that effect.
The marketing of OpenClaw is amazing. They had a one-liner install that didn't work, started the hype-train days before they changed the name of the product and have everyone from nerd influencers to CNBC raving about it.
> Anyone found some good use cases beyond a better interface for AI code assistance
Well... no. But I do really like it. It's just an always-on Claude you can chat with in Telegram, that tries to keep context, that has access to a ton of stuff, and it can schedule wakeup times for itself.
> Anyone found some good use cases beyond a better interface for AI code assistance?
Yesterday, I saw a demo of a product similar to OpenClaw. It can organize your files and directories and works really great (until it doesn't, of course). But don't worry, you surely have a backup and need to test the restore function anyway. /s
Edit:
So far, I haven’t found a practical use case for this. To become truly useful, it would need access to certain resources or data that I’m not comfortable sharing with it.
Our cognition evolves over time. That article was written when the Rabbit R1 presentation video was first released, I saw it and immediately reflect my thoughts on my blog. At that time, nobody had the actual product, let alone any idea how it actually worked.
Even so, I still believe the Rabbit has its merits. This does not conflict with my view that OpenClaw is what is truly useful to me.
I think this shows an unfettered optimism for things we don't know anything about. Many see this as a red flag for the quality of opinions.
> R1 is definitely an upgraded replacement for smartphones. It’s versatile and fulfills all everyday requirements, with an interaction style akin to talking to a human.
You seemed pretty certain about how the product worked!
> Today, Rabbit R1 has been released, and I view it as a milestone in the evolution of our digital organ.
You viewed it as a “milestone in the evolution of our digital organ” without you let alone anyone having even tested it?
Yet you say ”That article was written when the Rabbit R1 presentation video was first released, I saw it and immediately reflect my thoughts on my blog.”?
> Generally, I believe [Rabbit] R1 has the potential to change the world. This is a thought that seldom comes to my mind, as I have seen numerous new technologies and inventions. However, R1 is different; it’s not just another device to please a certain niche. It’s meticulously designed to serve one significant goal for all people: to improve lifestyle in the digital world.
What has this “team” actually achieved? I keep reading these manager cosplay blogs/tweets/etc but they aren’t ever about how a real team was replaced or how anything of significant complexity was actually built.
If my aim was to be a manager, I would have graduated a business university. But I want to have my hands and head dirty of programming, administering, and doing other technical stuff. I'm not going to manage, be it people or bots. So no, sorry.
And 99% those AI-created "amazing projects" are going to be dead or meaningless in due time, rather sooner than later. Wasted energy and water, not to mention the author's lifetime.
if 90% is good enough, you are a winner to try your idea and fail fast. if you want to reach 91 or more, AI is a slop and hype to burn our pensions and contribute to vastly to global warming and cognitive decline consumerism evolution
I think everyone cheering for AI will become its archenemy later. I’m very happy that companies like Salesforce and Duolingo, which fired so many people, are now tanking badly.
This euphoria quickly turns into disappointment once you finish scaffolding and actually start the development/refinement phase and claude/codex starts shitting all over the code and you have to babysit it 100% of the time.
That's a different problem and not really relevant to OpenClaw. Also, your issue is primarily a skills issue (your skills) if you're using one of the latest models on Claude Code or Codex.
You have to be joking. I tried Codex for several hours and it has to be one of the worst models I’ve seen. It was extremely fast at spitting out the worst broken code possible. Claude is fine, but what they said is completely correct. At a certain point, no matter what model you use, llms cannot write good working code. This usually occurs after they’ve written thousands of lines of relatively decent code. Then the project gets large enough that if they touch one thing they break ten others.
I beg to differ, and so do a lot of other people. But if you're locked into this mindset, I can't help you.
Also, Codex isn't a model, so you don't even understand the basics.
And you spent "several hours" on it? I wish I could pick up useful skills by flailing around for a few hours. You'll need to put more effort into learning how to use CLI agents effectively.
Start with understanding what Codex is, what models it has available, and which one is the most recent and most capable for your usage.
This reads like a peacocking LinkedIn post where someone desperately shows they are not just with it, they are ahead of it. The space is absolutely filled with this sort of noise, primarily people who dismissed AI as something only the nubs like, so now their cope is to do the "now it's useful and I have catapulted ahead of all the others bit".
This sort of post is useless without examples. What projects have you built? How did you go about it? What challenges did you face? What did you learn? Just saying “this is amazing now I am a super manager turning out projects left and right” is not convincing.
another slop post - show costs, show what you have built, or at least a tiny snippet of code? (or even just direct links to git repo or projects IN post please?)
been writing code for 15 years now , agree with the author about this one , open-claw like agents are going to be the future. Already automated away a bunch of routine stuff like checkin FB marketplace if l’m looking to but something , daily stock position brief , calendar management , grocery planning and buying , workout and calorie tracking . Stopped using a bunch of app directly overnight . The “mid-wits” are the one with their head still stuck under that sand
and the "hype-wits" don't realize openclaw is just claude with good mcp. there is nothing new under the sun. its just the first time someone was benevolent enough to open source the codebase to the public or it went viral enough to matter... and yet what people focus on is its "emergence" or "agi" - neither of which are remotely true. but good luck "crushing" those "mid-wits"
Yes claude + scripts without any big corp restrictions / bloat , if i want to connect to a website or api i can just do it. If you expose it to me as a human it is fair game for my assistant to read data the same way i do. Its like the old days of internet . I build harnesses for a living these days , i see why enterprises are slow to even to see what is possible
For the impatient, here's a transcript summary (from Gemini):
The speaker describes creating a "virtual employee" (dubbed a "replicant") running on a local server with unrestricted, authenticated access to a real productivity stack—including Gmail, Notion, Slack, and WhatsApp. Tasked with podcast production, the agent autonomously researched guests, "vibe coded" its own custom CRM to manage data, sent email invitations, and maintained a work log on a shared calendar. The experiment highlights the agent's ability to build its own internal tools to solve problems and interact with humans via email and LinkedIn without being detected as AI.
He ultimately concludes that for some roles, OpenClaw can do 90%+ of the work autonomously. Jason controversially mentions buying Macs to run Kimi 2.5 locally so they can save on costs. Others argue that hosting an open model on inference optimized hardware in the cloud is a better option, but doing so requires sharing potentially sensitive data.
I mean... If Jason Calacanis told me the sky was blue, I would be _checking_.
(At some point he seems to have gone from professionally-wrong-about-everything blogger to magical-podcast-thought-leader. I have no idea how this happened.)
As a real world example, I was told to evaluate Claude Code and ChatGPT codex at my current job since my boss had heard about them and wanted to know what it would mean for our operations. Our main environment is a C# and Typescript monorepo with 2 products being developed, and even with a pretty extensive test suite and a nearly 100 line "AGENTS.md" file, all models I tried basically fail or try to shortcut nearly every task I give it, even when using "plan mode" to give it time to come up with a plan before starting. To be fair, I was able to get it to work pretty well after giving it extremely detailed instructions and monitoring the "thinking" output and stopping it when I see something wrong there to correct it, but at that point I felt silly for spending all that effort just driving the bot instead of doing it myself.
It almost feels like this is some "open secret" which we're all pretending isn't the case too, since if it were really as good as a lot of people are saying there should be a massive increase in the number of high quality projects/products being developed. I don't mean to sound dismissive, but I really do feel like I'm going crazy here.
It's possible some of it is due to codebase size or tech stack, but I really think there might be more of a human learning curve going on here than a lot of people want to admit.
I think I am firmly in the average of people who are getting decent use out of these tools. I'm not writing specialized tools to create agents of agents with incredibly detailed instructions on how each should act. I haven't even gotten around to installing a Playwright mcp (probably my next step).
But I've:
- created project directories with soft links to several of my employer's repos, and been able to answer several cross-project and cross-team questions within minutes, that normally would have required "Spike/Disco" Jira tickets for teams to investigate
- interviewed codebases along with product requirements to come up with very detailed Jira AC, and then,.. just for the heck of it, had the agent then use that AC to implement the actual PR. My team still code-reviewed it but agreed it saved time
- in side projects, have shipped several really valuable (to me) features that would have been too hard to consider otherwise, like... generating pdf book manuscripts for my branching-fiction creating writing club, and launching a whole new website that has been mired in a half-done state for years
Really my only tricks are the basics: AGENTS.md, brainstorm with the agent, continually ask it to write markdown specs for any cohesive idea, and then pick one at a time to implement in commit-sized or PR-sized chunks. GPT-5.2 xhigh is a marvel at this stuff.
My codebases are scala, pekko, typescript/react, and lilypond - yeah, the best models even understand lilypond now so I can give it a leadsheet and have it arrange for me two-hand jazz piano exercises.
I generally think that if people can't reach the above level of success at this point in time, they need to think more about how to communicate better with the models. There's a real "you get out of it what you put into it" aspect to using these tools.
I can’t say it’s led to shipping “high quality projects”, but it has let me accomplish things I just wouldn’t have had time for previously.
I’ve been wanting to develop a plastic -> silicone -> plaster -> clay mold making process for years, but it’s complex and mold making is both art and science. It would have been hundreds of hours before, with maybe 12 hours of Claude code I’m almost there (some nagging issues… maybe another hour).
And I had written some home automation stuff back with Python 2.x a decade ago; it was never worth the time to refamiliarize myself with in order to update, which led to periodic annoyances. 20 minutes, and it’s updated to all the latest Python 3.x and modern modules.
For me at least, the difference between weeks and days, days and hours, and hours and minutes has allowed me to do things I just couldn’t justify investing time in before. Which makes me happy!
So maybe some folks are “pretending”, or maybe the benefits just aren’t where you’re expecting to see them?
- driving the LLM instead of doing it yourself. - sometimes I just can't get the activation energy and the LLM is always ready to go so it gives me a kickstart
- doing things you normally don't know. I learned a lot of command like tools and trucks by seeing what Claude does. Doing short scripts for stuff is super useful. Of course, the catch here is if you don't know stuff you can't drive it very well. So you need to use the things in isolation.
- exploring alternative solutions. Stuff that by definition you don't know. Of course, some will not work, but it widens your horizon
- exploring unfamiliar codebases. It can ingest huge amounts of data so exploration will be faster. (But less comprehensive than if you do it yourself fully)
- maintaining change consistency. This I think it's just better than humans. If you have stuff you need to change at 2 or 3 places, you will probably forget. LLM's are better at keeping consistency at details (but not at big picture stuff, interestingly.)
I'd previously encountered tools that seemed interesting, but as soon as I tried getting it to run I found myself going down an infinite debugging hole. With an LLM I can usually explain my system's constraints and the best models will give me a working setup from which I can begin iterating. The funny part is that most of these tools are usually AI related in some way, but getting a functional environment often felt impossible unless you had really modern hardware.
I use Claude Code a decent amount, and I actually find that sometimes this can be the opposite for me. Sometimes it is actually missing other areas that the change will impact and causing things to break. Sometimes when I go to test it I need to correct it and point out it missed something or I notice when in the planning phase that it is missing something.
However I do find if you use a more powerful opus model when planning, it does consider things fully a lot better than it used to. This is actually one area I have been seeing some very good improvements as the models and tooling improves.
In fact, I actually hope that these AI tools keep getting better at the point you mention, as humans also have a "context limit". There are only so many small details I can remember about the codebase so it is good if AI can "remember" or check these things.
I guess a lot of the AI can also depend on your codebase itself, how you prompt it, and what kind of agents file you have. If you have a robust set of tests for your application you can very easily have AI tools check their work to ensure things aren't being broken and quickly fix it before even completing the task. If you don't have any testing more could be missed. So I guess it's just like a human in some sense. If you have a crappy codebase for the AI to work with, the AI may also sometimes create sloppy work.
There is a counter issue though, realizing mid session that the model won’t be able to deliver that last 10%, and now you have to either grok a dump of half finished code or start from scratch.
For example a lot of pro-OpenAI astroturfing really wanted you to know that 5.3 scored better than opus on terminal-bench 2.0 this week, and a lot of Anthropic astroturfing likes to claim that all your issues with it will simply go away as soon as you switch to a $200/month plan (like you can't try Opus in the cheaper one and realise it's definitely not 10x better).
Since last few months, I have seen a notable difference in the quality and extent of projects these students have been able to accomplish. Every project and website they show looks polished, most of those could be a full startup MVP pre AI days.
The bar has clearly been raised way high, very fast with AI.
Once we got them into a technical screening, most fell apart writing code. Our problem was simple: using your preferred programming language, model a shopping cart object that has the ability to add and remove items from the cart and track the cart total.
We were shocked by how incapable most candidates were in writing simple code without their IDEs tab completion capability. We even told them to use whatever resources they normally used.
The whole experience left us a little surprised.
For the former, greenfield projects, LLMs are easily a 10x productivity improvement. For the latter, it gets a lot more nuanced. Still amazingly useful in my opinion, just not the hands off experience that building from scratch can be now.
usually when someone hypes it up it's things like, "i have it text my gf good morning every day!!", or "it analyzed every single document on my computer and wrote me a poem!!"
It does also seem to me that there is a lot of variance in skills for prompting/using AI in general (I say this as someone who is not particularly good as far as I’m aware – I’m not trying to keep tips secret from you). And there is also a lot of variance in the ability for an AI to solve problem of equal difficulty for a human.
Even if it's not straight astroturfing I think people are wowed and excited and not analyzing it with a clear head
That they are so good at the things I like to do the least and still terrible at the things at which I excel. That's just gravy.
But I guess this is in line with how most engineers transition to management sometime in their 30s.
The headline gain is speed. Almost no-one's talking about quality - they're moving too fast to notice the lack.
Given time AI will lead to incredible productivity. In the meantime, use as appropriate.
Tried to move some excel generation logic from epplus to closedxml library.
ClosedXml has basically the same API so the conversion was successful. Not a one-shot but relatively easy with a few manual edits.
But closedxml has no batch operations (like apply style to the entire column): the api is there but internal implementation is on cell after cell basis. So if you have 10k rows and 50 columns every style update is a slow operation.
Naturally, told all about this to codex 5.3 max thinking level. The fucker still succumbed to range updates here and there.
Told it explicitly to make a style cache and reuse styles on cells on same y axis.
5-6 attempts — fucker still tried ranges here and there. Because that is what is usually done.
Not here yet. Maybe in a year. Maybe never.
I then ask it to do the same thing in java, and it spends a half hour trying to do the same job and gets caught in some bit of trivia around how to convert html escape characters, for instance, s.replace("<", "<").replace(">", ">").replace("\"").replace("""); as an example and endlessly compiles and fails over and over again, never able to figure out what it has done wrong, nor decides to give up on the minutia and continue with the more important parts.
A giant monorepo would be a bad fit for an LLM IMO.
It's the appearance of productivity, not actual productivity.
Which I think is what people gather from him, but somehow think he's hiding it or pretending is not the case? Which I find strange, given how openly he's talked about it.
As for his productivity going down over time, I think that's a combination of his videos getting bigger scopes and production values, and also he moving some of his time into some not so publicly visible ventures. E.g., he was one of the founders of Standard, which eventually became the Nebula streaming service (though he left quite a while ago now).
The "open secret" is that shipping stuff is hard. Who hasn't bought a domain name for a side project that didn't go anywhere. If there's anybody out there, raise your hand! So there's another filtering effect.
The crazy pills are thinking that HN is in any way representative of anything about what's going on in our broader society. Those projects are out there, why do you assume you'll be told about it? That someone's going to write an exposé/blog post on themselves about how they had AI build a thing and now they're raking in the dollars and oh, buy my course on learning how to vibecode? The people selling those courses aren't the ones shipping software!
I don't doubt that an LLM would theoretically be capable of doing these sorts of things, nor did I intend to give off that sentiment, rather I was more evaluating if it was as practical as some people seem to be making the case for. For example, a C compiler is very impressive, but its clear from the blog post[0] that this required a massive amount of effort setting things up and constant monitoring and working around limitations of Claude Code and whatnot, not to mention $20,000. That doesn't seem at all practical, and I wonder if Nicholas Carlini (the author of the Anthropic post) would have had more success using Claude Code alongside his own abilities for significantly cheaper. While it might seem like moving the goalpost, I don't think it's the same thing to compare what I was saying with the fact that a multi billion dollar corporation whose entire business model relies on it can vibe code a C compiler with $20,000 worth of tokens.
> The problem is people have egos, myself included. Not in the inflated sense, but in the "I built a thing a now the Internet is shitting on me and I feel bad" sense.
Yes, this is actually a good point. I do feel like there's a self report bias at play here when it comes to this too. For example, someone might feel like they're more productive, but their output is roughly the same as what it was pre-LLM tooling. This is kind of where I'm at right now with this whole thing.
> The "open secret" is that shipping stuff is hard. Who hasn't bought a domain name for a side project that didn't go anywhere. If there's anybody out there, raise your hand! So there's another filtering effect.
My hand is definitely up here, shipping is very hard! I would also agree that it's an "open secret", especially given that "buying a domain name for a side project that never goes anywhere" is such a universal experience.
I think both things can be true though. It can be true that these tools are definitely a step up from traditional IDE-style tooling, while also being true that they are not nearly as good as some would have you believe. I appreciate the insight, thanks for replying.
[0]: https://www.anthropic.com/engineering/building-c-compiler
Also, there is nothing complex in a C compiler. As students we built these things as toy projects at uni, without any knowledge of software development practices.
Yet, to bring an example for something that's more than a toy project: 1 person coded this video editor with AI help: https://github.com/Sportinger/MasterSelects
> The reality: 3 weeks in, ~50 hours of coding, and I'm mass-producing features faster than I can stabilize them. Things break. A lot. But when it works, it works.
I used this line for a long time, but you could just as easily say the same thing for a typical engineer. It basically boils down to "Claude likes its tickets to be well thought out". I'm sure there is some size of project where its ability to navigate the codebase starts to break down, but I've fed it sizeable ones and so long as the scope is constrained it generally just works nowadays
Is it really to escape from "getting bogged down in the specifics" and being able to "focus on the higher-level, abstract work", to quote OP's words? I thought naively that engineering always has been about dealing with the specifics and the joy of problem solving. My guess is that the drive is toward power. Which is rather natural, if you think about it.
Science and the academic world
I have always failed to understand the obsessive dream of many engineers to become managers. It seems not to be merely about an increase in revenue.
Is it to escape from "getting bogged down in the specifics" and being able to "focus on the higher-level, abstract work", to quote OP's words? I thought naively that engineering has always been about dealing with the specifics and the joy of problem-solving. My guess is that the drive is towards power, which is rather natural, if you think about it.
Science and the academic world suffer a comparable plague.
And when you're in an existing company, stuck in thing X, knowing that it's obsolete, and the people doing the latest Y that's hot in the job market are in another department and jealously guard access to Y projects?
How about when you go to interview, and you not ONLY have to know Y, but the Leetcode from 15 years ago?
So maybe I've given you another alternative to 'it has to be power, there's no other rational reason to go into management'.
Here's a gentler one: if you want to build big things, involving many people, you need to be in management.
Do you enjoy brick laying and calculating angles around doorways? You're the engineer. Do you want to be the architect hiring engineers, working with project managers, and assessing the budget while worrying about approvals? They're different types of work, and it's not about 'power' like you are suggesting. Autonomy and decision-making power are more the 'power' engineers often don't get (unless they are lucky, very very smart or in a small startup-like environment).
I've gone back and forth across the lead and management lines many times now, and it is career limiting in many many ways. But it's too fulfilling to give up. And I swear there is magic in what small, expert groups are able to produce that laps large org on the regular.
Some research around British government workers found higher job satisfaction in units with hands-off managers. It resonates with my own career. I’m really excited and want to go to work when I’m on a small, autonomous team with little red tape and politics. Larger orgs simply can’t — or haven’t — ever offered me the same feeling; with some exceptions in Big 3 consulting if I was the expert on a case.
The worst manager is the micromanager - either because he's nervous about his job security, because he doesn't know how to delegate, or because he's been hands-on forever and can't let go.
I don't see why it contradicts my little rant above. Of course I also prefer small, nimble teams with lots of autonomy, with individuals who thrive being delegated only extremely broad tasks. The only part where I think there's a difference is the constantly learning.
I love constantly learning. My issue isn't that. It's that I don't want to HAVE to constantly be practicing at home and on the weekend. I did this in my 20s and I can't/won't do this anymore. I just have no time or energy now as an Old.
For myself it is the hands-on work I find most fulfilling unfortunately. I have some sort of brain worm that makes me want to practice all the new things at home/weekend if work isn't letting me. I'm sure it'll burn me out at some point, but to paraphrase a famous creep: I keep getting older, my brainworm stays the same age.
Within my power I try to do that with my directs, making sure new interesting things are cycled in so their CVs become stronger. But me, personally, I've had really bad luck with this. I always had to study on the weekends for something that either isn't used in my company or someone else jealously guards because it's hot on the market.
Web servers have existed for more than 30 years and haven’t changed that much since then. Or e.g., React + Redux is pretty much the same thing as WinProc from WinAPI - invented some time in ~1990. Before Docker, there were Solaris Zones and FreeBSD jails. TCP/IP is 50 years old. And many, many other things we perceive as new.
Moreover, I think it’s worth looking back and learning some of the “old tech” for inspiration; there’s a wealth of deep and prescient ideas there. We still don’t have a full modern equivalent of Macromedia Flash, for example.
I can't tell if this is sincere or parody, it is so insufferably wrong. Good troll. I almost bit.
https://news.ycombinator.com/item?id=10381015
Almost nothing goes obsolete in software; it just becomes unpopular. You can still write every website you see on the Internet with just jQuery. There are perfectly functional HTTP frameworks for Cobol.
I am scientist and worked from time to time as a research engineer merely to pay the bills, so I may see things differently. I always like doing lab / field work and first-hand data analysis. Many engineers I know would likely never stop tinkering and building stuff. It may be easier for a scientist than for an engineer to still get trilled, I don't know.
These are inherently different levels of power. I'm not sure how your example is supposed to be the opposite when you compare someone laying bricks to someone making hiring and firing decisions about groups of people. Your scenario is fundamentally a power imbalance
If only the world incentivized ICs with depth of knowledge to stay in those roles for the long haul instead of chopping off our knowledge of specificity at the apex of their depth of knowledge. So many managers have no talent, no depth of knowledge and a passable ability to manage people.
That sure beats having it completely obsoleted a few weeks later, which sometimes feels like the situation with AI
It's a skill that takes practice -coordinating disparate people and groups, creating communication where you notice they're not talking to each other, creating or fixing processes that annoy or cause chaos if they're not there, encouraging people, being a therapist, seeing what's not there and pushing a vision while you get the group to go along, protecting people from management above and pressures around, etc are mostly skills that you learn.
Sometimes no one will give you feedback so you have to figure it out yourself (unless you're lucky to get a mentor), so you just have to throw yourself in and give yourself grace to fail and succeed over time.
The only skill of these I think is possibly genetic or innate, is being able to see the big picture and make strategical decisions. A lot of tech people skew cognitively in narrow areas, and have trouble conceptualizing the world beyond.
One challenge here is the ubiquitous 'managers just approve vacations and waste space' sentiment on here and in some places. These people are a chore to manage (and sometimes are better not being present in your group).
No, you don’t. You need some kind of decision making and communication process but a separate management is not necessary.
Do you know what stank ranking even is and where it comes from? If you have to rate your group from 1 to 5, each individual, and you rate them all 4s and 5s, they crack down and force you to select a 2 and a 3 and only have one 5. Now, would you prefer a CFO, CTO or even a project manager be the one to do it? It's a weird comment.
Again, as an older manager today, I can see myself in my 20s in the resistance and stubbornness to 'how corporations work' espoused in comments like yours. I sympathize, but I warn you against being naive and ideological, because unfortunately human groups be human groups, and organizations for better or for worse behave in predictable patterns. You might as well know as much as possible so you can deal with it better.
Real managers deal with coaching, ownership, feelings, politics, communication, consensus building, etc. The people who are good at it like setting other people up to win.
> I’d think there would be very, very few people who are actively seeking people drama
Theoretically as a manager you get the bump up the power dynamic ladder (and probably pay ladder) because you are taking on the responsibility of "people drama". Being a good manager is antithetical to treating living, breathing human beings as NPCs in a game.
Often too it's the architecture that can cause a grand idea to crash and burn—experienced devs should be moving toward solving those problems.
Like I’ve been in situations as an IC where poor leadership from above has literally caused less efficient and more painful day-to-day work. I always hoped I could sway those decisions from my position as an IC, but reality rarely aligned with that hope.
I actually love the details, but I just don’t get too deep into them these days as I don’t want to micro-manage.
I do find I have more say in things my team deals with now that I’m a manager.
That can extend to arbitrary absurdity. You are probably not growing your own food, mining your own ore, forging your own tools, etc etc etc.
It's all just a matter of where you rely on external tools/abstractions to do parts of the work you don't want to do yourself.
It's frontier exploration that brings me joy. If a clanker can do something, then it's a solved problem. I use all the tools at my disposal to push the frontier of problems solved. Wasting my time re-inventing the wheel brings me the opposite of joy.
But I'm acutely conscious that in the 5+ years that I've been a senior developer, my ability to come up with useful ideas has significantly outstripped the time I have to realize those ideas (and from experience, the same is often true of academics).
At work, I have the choice between remaining hands-on and limiting what I can get done, or acting more like a manager, and having the opportunity to get more done, but only by letting other people do it, in ways that might not reflect my vision. It's pretty frustrating, to be honest.
For side projects, it's worse. Most of them just can't be done, because I don't even have the choice.
I was recently looking for mentors to work with him and advance his skills, targeting college aged kids / young 20s..
It was surprising to me how many people I came across in this field at this young age that are trying to focus on the "higher level" game planning aspects and not so much on the lower level implementation specifics.
https://www.youtube.com/playlist?list=PLnuhp3Xd9PYTt6svyQPyR...
https://guide.handmadehero.org/hmcon/
https://guide.handmadehero.org/
https://handmade.network/forums
I think it's that there is only that much demand for solving really complex problems, and doing the same thing over and over is boring, so management is the only way forward for many people
https://en.wikipedia.org/wiki/The_Stonecutter
You want to write a book about people's deepest motivations. Formative experiences, relationships, desires. Society, expectations, disappointment. Characters need to meet and talk at certain times. The plot needs to make sense.
You bring it to your editor. He finds you forgot to capitalise a proper noun. You also missed an Oxford comma. You used "their" instead of "they're".
He sends you back. You didn't get any feedback about whether it makes sense that the characters did what they did.
You are in hell, you won't hear anything about the structure until you fix your commas.
Eventually someone invents an automatic editor. It fixes all the little grammar and spelling and punctuation issues for you.
Now you can bring the script to an editor who tells you the character needs more development.
You are making progress.
Your only issue is the Luddites who reckon you aren't a real author, because you tend to fail their LeetGrammar tests, calling you a vibe author.
You can't do that from a high level abstract position. You actually need to stand at the coal face and think about it from time to time.
This article encodes an entitled laziness that's destructive to personal skill and quality work.
A few years ago, when Agile was still the hot thing and companies had an Agile "facilitor" or manager for each dev team, the common career path I heard when talking to those people was: "I worked as a java/cobol/etc in the past, but it just didn't click with me. I'm more of a peoples person, you know, so project management is where I really do my best work!".
Yeah, right...
> This has truly freed up my productivity, letting me pursue so many ideas I couldn’t move forward on before
If you're writing in a blog post that AI has changed your life and let you build so many amazing projects, you should link to the projects. Somehow 90% of these posts don't actually link to the amazing projects that their author is supposedly building with AI.
I've got 10+ years of coding experience, I am an AI advocate, but not vibe coding. AI is a great tool to help with the boring bits, using it to initialize files, help figure out various approaches, as a first pass code reviewer, helping with configuring, those things all work well.
But full-on replacing coders? It's not there yet. Will require an order of magnitude more improvement.
I am using them in projects with >100kloc, this is not my experience.
at the moment, I am babysitting for any kloc, but I am sure they will get better and better.
> Somehow 90% of these posts don't actually link to the amazing projects that their author is supposedly building with AI.
You are in the 90%.
I am sure there are ways to get around this sort of wall, but I do think it's currently a thing.
I built a skribbl.io clone to use at work. We like to play eod on Friday as a happy hour and when we would play skribbl.io we would try to get screencaps of the stupid images we were drawing but sometimes we would forget. So I said I'd use claude to build our own skribbl.io that would save the images.
I was definitely surprised that claude threaded the needle on the task pretty easily, pretty much single shot. Then I continued adding features until I had near parity. Then I added the replay feature. After all that I looked at the codebase... pretty much a single big file. It worked though, so we played it for the time being.
I wanted to fix some bugs and add more features, so I checked out a branch and had an agent refactor first. I'd have a couple context/sessions open and I'd one just review, the other refactored, and sometimes I'd throw a third context/session in there that would just write and run tests.
The LLM will build things poorly if you let it, but it's easy to prompt it another way and even if you fail that and back yourself into a corner, it's easy to get the agents to refactor.
It's just like writing tests, the llms are great at writing shitty useless tests, but you can be specific with your prompt and in addition use another agent/context/session to review and find shitty tests and tell you why they're shitty or look for missing tests, basically keep doing a review, then feed the review into the agent writing the tests.
That said, I do catch it doing some of the stuff the OP mentioned— particularly leaving “backwards compatibility” stuff in place. But really, all of the stuff he mentions, I’ve experienced if I’ve given it an overly broad mandate.
You also need a reasonably modular architecture which isn't incredibly interdependent, because that's hard to reason about, even for humans.
You also need lots and lots (and LOTS) of unit tests to prevent regressions.
Surely it depends on the design. If you have 10 10kloc modular modules with good abstractions, and then a 10k shell gluing them together, you could build much bigger things, no?
Then again the problem is that the public has learned nothing from the theranos and WeWorks and even more of a problem is that the vc funding works out for most of these hype trains even if they never develop a real business.
The incentives are fucked up. I’d not blame tech enthusiasts for being too enthusiastic
Might as well talk about how AI will invent sentient lizards which will replace our computers with chocolate cake.
Thinking usually happens inside your head.
What is your point?
If you’re trying to say that they should have kept their opinion to themselves, why don’t you do the same?
Edit: tone down the snark
Holy Spiderman what is your point? That if someone says something dumb I can never challenge them nor ask them to substantiate/commit?
> tone down the snark
It's amazing to me that the neutral observation "thinking happens in your head" is snarky. Have you ever heard the phrase "tone police"?
If you spend a couple of years with an LLM really watching and understanding what it’s doing and learning from mistakes, then you can get up the ladder very quickly.
A "basic" understanding in critical domains is extremely dangerous and an LLM will often give you a false sense of security that things are going fine while overlooking potential massive security issues.
All I could think was, "good luck" and I certainly hope their app never processes anything important...
I don't feel like most providers keep a model for more than 2 years. GPT-4o got deprecated in 1.5 years. Are we expecting coding models to stay stable for longer time horizons?
If the person who is liable for the system behavior cannot read/write code (as “all coders have been replaced”), does Anthropic et al become responsible for damages to end users for systems its tools/models build? I assume not.
How do you reconcile this? We have tools that help engineers design and build bridges, but I still wouldn’t want to drive on an “autonomously-generated bridge may contain errors. Use at own risk” because all human structural engineering experts have been replaced.
After asking this question many times in similar threads, I’ve received no substantial response except that “something” will probably resolve this, maybe AI will figure it out
SHOW ME THE MONEY!!!
Maybe they don't feel like sharing yet another half working Javascript Sudoku Solver or yet another half working AI tool no one will ever use?
Probably they feel amazed about what they accomplished but they feel the public won't feel the same.
GPT-5.2 fixed my hanging WiFi driver: https://gist.github.com/lostmsu/a0cdd213676223fc7669726b3a24...
It's a magical moment when someone is able to AI code a solution to a problem that they couldn't fix on their own before.
It doesn't matter whether there are other people who could have fixed this without AI tools, what matters is they were able to get it fixed, and they didn't have to just accept it was broken until someone else fixed it.
Cue the folks saying "well you could DIE!!!" Not if I don't fix brakes, etc ...
What type of code? What types of tools? What sort of configuration? What messaging app? What projects?
It answers none of these questions.
I'm now using pi (the thing openclaw is built on) and within a few days i build a tmux plugin and semaphore plugin^1, and it has automated the way _I_ used to use Claude.
The things I disagree with OP is: The usefulness of persistent memory beyond a single line in AGENTS.md "If the user says 'next time' update your AGENTS.md", the use of long-running loops, or the idea that everything can be resolved via chat - might be true for simple projects, but any original work needs me to design the 'right' approach ~5% of the time.
That's not a lot, but AI lets you create load-bearing tech-debt within hours, at which point you're stuck with a lot of shit and you dont know how far it got smeared.
[1]: https://github.com/offline-ant
(Not necessarily this specific post).
>Over the past year, I’ve been actively using Claude Code for development. Many people believed AI could already assist with programming—seemingly replacing programmers—but I never felt it brought any revolutionary change to the way I work.
Funny, because just last month, HN was drowning in blog posts saying Claude Code is what enables them to step away from the desk, is definitely going to replace programmers, and lets people code "all through chatting on [their] phone" (being able to code from your phone while sitting on the bus seems to be the magic threshold that makes all the datacenters worth it).
This is an AI generated post likely created by going to chatgpt.com and typing in "write a blogpost hyping up [thing] as the next technological revolution", like most tech blog content seems to be now. None of those things ever existed, the AI made them up to fulfill the request.
To add to this, OpenClaw is incapable of doing anything meaningful. The context management is horrible, the bot constantly forgets basic instructions, and often misconfigures itself to the point of crashing.
edit: love the downvotes. I guess HN really is Reddit now. You can make any accusation without evidence and people are supposed to just believe it. If you call it out you get downvoted.
Besides, if there are enough red flags that make it indistinguishable from actual AI slop, then chances are it's not worth reading anyway and nothing of value was lost by a false positive.
It's like we all fell under the spell of a terminal endlessly printing output as some kind of measurement of progress.
I just give the link to those posts to my AI to read it, if it's not worth a human writing it, it's not worth a human reading it.
The only software I've seen designed and implemented by OpenClaw is moltbook. And I think it is hard to come up with a bigger pile of crap than Moltbook.
If somebody can build something decent with OpenClaw, that would help add some credibility to the OpenClaw story.
They are not able to comprehend that for anything more complicated than that, the code might compile, but the logical errors and failure to implement the specs start piling up.
Grok 4 Fast told me its own internal system prompt has rules against autonomous operation, so that might have something to do with it. I am having decent results with it though.
I let it run in a VM on my desktop and I can check on its progress and provide feedback any time. Only took a few iterations of telling it to tweak its workflow to land on something very productive. Doesn't work for everything but it covers a lot of my work.
For me the pain point has always been with non-IT people/companies. They are way more accustomed with phone or even in person appointments. They in general have way more of a say than me, the customer.
Can Openclaw make and take phone calls for me to make appointments? Can Openclaw do chores for me? Can Openclaw meet with contractors for me? None of them it can do. It can make notes for me (useless as most notes are useless). It can scrap websites for me (not very interesting as why would I want to collect so much knowledge?). It can probably automate anything that already has an endpoint or whatever, but I don’t mind write code for my own projects. I always failed to understand why anyone would want to let AI write most of the code of their PERSONAL project — unless they want to sell them quickly.
I’m just a frustrated old man I guess.
[0] https://vapi.ai/
> I’m just a frustrated old man I guess.
I think this is a great summary of the failure of vision that a lot of tech people are having right now.
> automate anything that already has an endpoint or whatever
Facebook used to have API's, Reddit used to have API's, amazon used to have API's
They are gone.
Enshitification and dark patterns have taken over.
"Hey open claw, cancel service xxx" where XXX is something that is 17 steps and purposely hard to cancel so they keep your money.
What's going to happen when your AI tool can go to a website and strip the ad's off and return you just the text? What happens when it can build a customized news feed that looks less like Facebook and more like HN? Aren't we just gaining back function we lost with the death of RSS?
Consumers are mad about the hype of AI but the moment that it can cut through the bullshit we keep putting in their way it's going to wreck business MODELS, and the choice will be adapt or die. Start asking your "AI" tools to do all the basic, tedious bullshit tasks that are low risk (you have a ton of them) and if it gets 1/4 of them done your going to free up a ton of your own time.
[1] https://reorx.com/blog/rabbit-r1-the-upgraded-replacement-fo...
I tried using LLMs to help debug at different points, but they went in circles on bad ideas, even when I gave them what turned out to be a correct clue.
Root cause turned out to be that IPv6 wasn't enabled for Docker networking, but was enabled for the websites DNS. So people who connected over IPv6 were getting their IPs all converted to the same internal Docker IP before being handed to the per-IP throttling algorithm.
I spotted that there were no IPv6 IPs in the logs, but the LLMs missed that the key pattern was the absence of something expected, instead drawing wrong conclusions.
So no, I'm not about to turn OpenClaw loose on building anything at all complex.
> OpenClaw gave me the chance to become that super manager [...] A manager shouldn’t get bogged down in the specifics—they should focus on the higher-level, abstract work
These two propositions seem to be highly incompatible
Regardless of how you isolate the OpenClaw instance (Mac Mini, VPS, whatever) - if it’s allowed to browse the web for answers then there’s the very real risk of prompt injection inserting malicious code into the project.
If you are personally reviewing every line of code that it generates you can mitigate that, but I’d wager none of these “super manager” users are doing that.
1. It has a lot of files that it loads into it's context for each conversation, and it consistently updates them. Plus it stores and can reference each conversation. So there's a sense of continuity over time.
2. It connects to messaging services and other accounts of yours, so again it feels continuous. You can use it on your desktop and then pick up your phone and send it an iMessage.
3. It hooks into a lot of things, so it feels like it has more agency. You could send it a voice message over discord and say "hey remember that conversation about birds? Send an email to Steve and ask him what he thinks about it"
It feels more like a smart assistant that's always around than an app you open to ask questions to.
However, it's worth stressing how terrible the software actually is. Not a single thing I attempted to do worked correctly, important issues (like the discord integration having huge message delays and sometimes dropping messages) get closed because "sorry we have too many issues", and I really got the impression that the whole thing is just a vibe coded pile of garbage. And I don't like to be that critical about an open source project like this, but I think considering the level of hype and the dramatic claims that humans shouldn't be writing code anymore, I think it's worth being clear about.
Ended up deleting it and setting up something much simpler. I installed a little discord relay called kimaki, and that lets me interact with instances of opencode over discord when I want to. I also spent some time setting up persistent files and made sure the llm can update them, although only when I ask it to in this case. That's covered enough of what I liked from OpenClaw to satisfy me.
Ah, so it's a device for irritating Steve, got it.
if one of my friends sent me an obviously AI-written email, I think that I would cease to be friends with them...
Isn’t the “what he thinks about it” part the hardest? Like, that’s what I want to phrase myself - the part of the conversation I’d like to get their opinion on and what exactly my actual request is. Or are people really doing the meme of sending AI text back and forth to each other with none the wiser?
For personal communication between friends it would be horrible. Authenticity has to be one of the things I value most about the people I know. Didn't mean to imply from that example that I did or would communicate that way.
https://github.com/a-n-d-a-i/ULTRON
Well, it's a work in progress, but I have self-upgrading and self-restarting working, and it's already more reliable than Claw ;)
I used the Claude Code SDK (Agents SDK) originally, but then realized I can get the same result by just calling `claude -p the_telegram_message`
The magic sauce being the --continue flag, of course. Bit less useful otherwise.
I haven't figured out how to interrupt it or see what it's doing yet though.
Honestly I'd rather die
> Rabbit R1 - The Upgraded Replacement for Smart Phones
Kinda hard to take anything here seriously.
I don't know about this; or at least, in my experience, is not a what happens with good managers.
I guess best managers just develop the hunch and know when to do this and when to ask engineers for smallest details to potentially develop different solutions. You have to be technical enough to do this
That would be really helpful.
Why isn't Claude doing all that for me, while I code? Why the obsession that we must use code generation, while other gabage activities would free me to do what I'm, on paper, paid to do?
It's less sexy of course, it doesn't have the promise of removing me in the end. But the reason, in the present state, is that IT admins would never accept for an llm to handle permissions, rotations, management would never accept an llm to report status or provide estimate. This is all "serious" work where we can't have all the errors llm create.
Dev isn't that bad, devs can clean slop and customers can deal with bugs.
Good luck hoping that none from the big money would try to stand between you and someone giving you a service (uber, airbnb, etsy, etc) and get rent from that.
Claude, fix the toilet.
This has been a significant aspect of ai use as well. As a result a feel a little less friction with myself, less that I am letting things slip by because, well, because I still want a nice balance to work, life, leisure, etc. I don’t want to overstate things, it’s not a cure all for any of these things, but it helps a lot.
I feel like there's this "secret" hiding behind all these AI tools, that actually it's all very complicated and takes a lot of effort to make work, but the tools we're given hides it all. It's nice that we benefit from its simplicity of use. But hiding complexity leads to unexpected problems, and I'm not sure we've seen any of those yet - other than the massive, gaping security hole.
And me ruining my day fighting with a million hooks, specs and custom linters micromanaging Claude Code in the pursuit of beautiful code.
> Generally, I believe (Rabbit) R1 has the potential to change the world.
There is a pattern here.
I'm not running OpenClaw, but I've given Claude its own email address and built a polling loop to check email & wake Claude up when I've sent it something. I'm finding a huge improvement from that. Working via email seems to change the Claude dynamic, it feels more like collaborating with a co-worker or freelancer. I can email Claude when I'm out of the house and away from my computer, and it has locked down access to use various tools so it can build some things in reply to my emails.
I've been looking into building out voice memos or an Eleven Labs setup as well, so I can talk to Claude while I'm out exercising, washing dishes etc. Voice memos will be relatively easy but I haven't yet got my head around how to integrate Eleven Labs and work with my local data & tools (I don't want a Claude that's running on Eleven Labs servers).
What made it so popular I think is that it made it easy to attach it to whatever "channel" you're comfortable with. The mac app comes with dictation, but unsure the amount of setup to get tts back.
So, OpenClaw has changed his life: It has accelerated the AI psychosis.
I saw on The Verve that they partnered with the company that repeatedly disclosed security vulnerabilities to try to make skills more secure though which is interesting: https://openclaw.ai/blog/virustotal-partnership
I’m guessing most of that malware was really obvious, people just weren’t looking, so it’s probably found a lot. But I also suspect it’s essentially impossible to actually reliably find malware in LLM skills by using an LLM.
A Reddit post with white invisible text can hijack your agent to do what an attacker wants. Even a decade or 2 back, SQL injection attacks used to require a lot of proficiency on the attacker and prevention strategies from a backend engineer. Compare that with the weak security of so called AI agents that can be hijacked with random white text on an email or pdf or reddit comment
It cannot. This is the security equivalent of telling it to not make mistakes.
> Restrict downstream tool usage and permissions for each agentic use case
Reasonable, but you have to actually do this and not screw it up.
> Harden the system according to state of the art security
"Draw the rest of the owl"
You're better off treating the system as fundamentally unsecurable, because it is. The only real solution is to never give it untrusted data or access to anything you care about. Which yes, makes it pretty useless.
I have OPA and set policies on each tool I provide at the gateway level. It makes this stuff way easier.
It does not. Security theater like that only makes you feel safer and therefore complacent.
As the old saying goes, "Don't worry, men! They can't possibly hit us from this dist--"
If you wanna yolo, it's fine. Accept that it's insecure and unsecurable and yolo from there.
I never want to be one wayward email away from an AI tool dumping my company's entire slack history into a public github issue.
I haven't been able to find a good use for myself yet. Almost everything I use an LLM for has some kind of hard human-in-the-loop factor that is as of yet inescapable -- but I also don't really use LLMs for things like "sort my email.". mostly entirely coding.
So, it appears that we have come a long way bubbling up through abstraction layers: assembly code -> high-level languages -> scripting -> prompting -> openclaw.
It's the endgame.
> Then OpenClaw came along, and everything changed.
> After a few rounds of practice, I found that I could completely step away from the programming environment and handle an entire project’s development, testing, deployment, launch, and usage—all through chatting on my phone.
So, with Claude Code, you're stuck typing in a chat box. Now, with OpenClaw, you can type in a chat box on your phone? This is exciting and revolutionary.
oh man this is fantastic
Something tells me they never even downloaded OpenClaw before writing this blog post. It’s probably an aspirational vision board type post their life coach told them to write because they kept talking about OepnClaw during their sessions, and the life coach got tired of their BS.
https://www.rabbit.tech/rabbit-r1
No desire to be a hater or ignore the possibility of any tech but…yeah…transformative that was not
It's a racket never ends.
It is a constant lure products and tools have to create the feeling of sensemaking. People want (pejorative) tools that show visualizations or summaries, without thinking about the particular visual/summary artifact is useful, actionable or accurate!
They (or their devs) are not at fault that some people honestly believe you can't be as productive or consistent without a "thought garden" or whatever.
It only becomes problematic if the “good” thing also indulges in the hubris of influencers because they view it as good marketing. Like when an egg farm leans in “orange yolk”
Most famously, patio11 makes it a definitive part of his writing style.
I agree it's a terrible use of quotation marks, but it's a widely-used style I've been forced to accept.
https://reorx.com/blog/rabbit-r1-the-upgraded-replacement-fo...
What I really wonder, is who the heck is upvoting this slop on hackernews?
So many wealthy players invested the outcome, and the technology for astroturfing (LLMs) can ironically be used to boost itself and further its own development
Articles like these should be flagged, and typically would be, but they sometimes appear mysteriously flag-proof.
Even then, the architecture will be horrible unless you chat _a lot_ about it upfront. At some point, it’s easier to just look in the terminal.
Maybe it's unfair to judge an author's current opinion by their past opinion - but since the piece is ultimately an opinion based on their own experience I'm going to take it along a giant pile of salt that the author's standards for the output of AI tools are vastly different than mine.
The last time I talked to someone about OpenClaw and how it is helping them, they told me it tells them what their calendar has for them today or auto-tweets for them (i.e., non-human spam). The first is as simple as checking your calendar, and the second is blatant spam.
Anyone found some good use cases beyond a better interface for AI code assistance?
Their example use case was for it to read and summarize our Slack alerts channel to let us know if we had any issues by tagging people directly... the Slack channel is populated by our monitoring tools that also page the on-call dev for the week.
The kicker... this guy was the on-call dev that week and had just been ignoring the Slack channel, emails and notifications he was getting!
This should be the opening for every post about the various "innovations" in the space.
Preferably with a subsequent line about the manual process that was worth putting the extra effort into prior to the shiny new thing.
I really can imagine a better UX then opening my calendar in one-click and manual scanning.
Another frequent theme is "tell me the weather." One again, Google home (alexa or whatever) handles it while I'm still in bed and let's me go longer without staring at a screen.
The spam use-case is probably the best use-case I've seen, as in it truly saves time for an equal or better result, but that means being cool with being a spammer.
I'm not running openclaw itself. I am building a simpler version that I trust and understand a lot more but ostensibly it's just another always on Claude code wrapper.
I can't come up with any other explanation for why there seems to be so many people claiming that AI is changing their life and workflow, as if they have a whole team of junior engineers at their disposal, and yet have really not that much to show for it.
They're so white collar-pilled that they're in utter bliss experiencing a simulation of the peak white collar experience, being a mid-level manager in meetings all day telling others what to do, with nothing tangible coming out of it.
To be specific, for the past year I've been having numerous long conversations about all the books I've read. I talk about what I liked, didn't like, the ideas and and plots I found compelling or lame, talks about the characters, the writing styles of authors, the contemporary social context the authors might have been addressing, etc. Every aspect of the books I can think off. Then I ask it for recommendations, I tell it given my interests and preferences, suggest new books with literary merit.
ChatGPT just knocks this out of the park, amazing suggestions every time, I've never had so much fun reading than in the past year. It's like having the world's best read and most patient librarian at your personal disposal.
My experience with plain Claude Code is that I can step back and get an overview of what I'm doing, since I tend to hyperfocus on problems, preventing me from having a simultaneous overview.
It does feel like being a project manager (a role I've partially filled before) having your agency in autopilot, which is still more control than having team members do their thing.
So while it may feel very empowering to be the CEO of your own computer, the question is if it has any CEO-like effect on your work.
Taking it back to Claude Code and feeling like a manager, it certainly does have a real effect for me.
I won't dispute that running a bunch of agents in sync won't give you an extension of that effect.
The real test is: Do you invoice accordingly?
I'm waiting for the grift!
Well... no. But I do really like it. It's just an always-on Claude you can chat with in Telegram, that tries to keep context, that has access to a ton of stuff, and it can schedule wakeup times for itself.
Yesterday, I saw a demo of a product similar to OpenClaw. It can organize your files and directories and works really great (until it doesn't, of course). But don't worry, you surely have a backup and need to test the restore function anyway. /s
Edit:
So far, I haven’t found a practical use case for this. To become truly useful, it would need access to certain resources or data that I’m not comfortable sharing with it.
Yes I think it is
And one sided media does as weil. Or do you expect Fox News to publish an unbiased report just next?
Even so, I still believe the Rabbit has its merits. This does not conflict with my view that OpenClaw is what is truly useful to me.
> R1 is definitely an upgraded replacement for smartphones. It’s versatile and fulfills all everyday requirements, with an interaction style akin to talking to a human.
You seemed pretty certain about how the product worked!
We're allowed to have opinions about promises that turn out not to be true.
If the rabbit had been what it claimed it would be, it would have been an obvious upgrade for me, at least.
I just want a voice-first interface.
The most charitable thing you can say about this is they're naive, ignorant of the history of vapourware 'demoed' at trade shows.
> Today, Rabbit R1 has been released, and I view it as a milestone in the evolution of our digital organ.
You viewed it as a “milestone in the evolution of our digital organ” without you let alone anyone having even tested it?
Yet you say ”That article was written when the Rabbit R1 presentation video was first released, I saw it and immediately reflect my thoughts on my blog.”?
> Generally, I believe [Rabbit] R1 has the potential to change the world. This is a thought that seldom comes to my mind, as I have seen numerous new technologies and inventions. However, R1 is different; it’s not just another device to please a certain niche. It’s meticulously designed to serve one significant goal for all people: to improve lifestyle in the digital world.
I hope at some point there will be a medical research into this hysteria.
There's not a single real example, and it even has all the em-dashes intact.
Agents work but still mostly produce slop.
Poe's law strikes... I can't tell if this is satire.
And 99% those AI-created "amazing projects" are going to be dead or meaningless in due time, rather sooner than later. Wasted energy and water, not to mention the author's lifetime.
If you delegate these tasks to OpenClaw, I am not really sure the result is exactly what you want to achieve and it works like you want it to.
Also, Codex isn't a model, so you don't even understand the basics.
And you spent "several hours" on it? I wish I could pick up useful skills by flailing around for a few hours. You'll need to put more effort into learning how to use CLI agents effectively.
Start with understanding what Codex is, what models it has available, and which one is the most recent and most capable for your usage.
Press [Space] to skip
getting sick of this fluff stuff
For the impatient, here's a transcript summary (from Gemini):
He ultimately concludes that for some roles, OpenClaw can do 90%+ of the work autonomously. Jason controversially mentions buying Macs to run Kimi 2.5 locally so they can save on costs. Others argue that hosting an open model on inference optimized hardware in the cloud is a better option, but doing so requires sharing potentially sensitive data.(At some point he seems to have gone from professionally-wrong-about-everything blogger to magical-podcast-thought-leader. I have no idea how this happened.)