The way Claude Code is going is exactly what I want out of a agentic coding tool with this "unix toolish" philosophy. I've been using Claude code since the initial public preview release, and have seen the direction over time.
The "golden" end state of coding agents is that you give it a Feature Request (EG Jira ticket), and it gives you a PR to review and give feedback on. Cursor, windsurf, etc, are dead ends in that sense as they are local editors, and can not be in CI.
If you are tooling your codebase for optimal AI usage (Rules, MCP, etc), you should target a technology that can bridge the gap to headless usage. The fact Claude Code can trivially be used as part of automation through the tools means it's now the default way I thinking about coding agents (Codex, the npm package, is the same).
Disclaimer, I focus on helping companies tool their codebases for optimal agent usage, so I might have a bias here to easily configurable tools.
Not sure about that golden end state. Mine would be being in a room surround by screens with AI agents coding, designing, testing, etc. I would be there in the center giving guidance, direction, applying taste, etc…
All conversational, wouldn’t need to touch the keyboard 99% of the time.
I hate using voice for anything. I hate getting voice messages, I hate creating them. I get cold sweats just thinking about having to direct 10 AI Agents via voice. Just give me a keyboard and a bunch of screens, thanks.
I’m the same. I love that writing allows you to think while typing so that you can review and revise your thoughts before letting them out in the world.
And don’t get me started on video vs text for learning purely non-physical stuff like programming…
Voicemail universally sucks. However, when you're having a synchronous conversation with actual people, do you prefer to do everything via IM, or would you prefer a phone call?
Email. Async comms make sense 99% of the time at my job. Unless there's deep work to be done, or pie-in-the-sky idea fabricating. Or rubber-ducky sessions. But I won't do those with AI.
Email is Calm Technology[0] for collaborative knowledge work, where you expected to spend hours on a single task. If something needs brainstorming, or quick back and forth, you jump on a more synchronous type of conversation (IM, call, in person meeting).
I almost never prefer a phone call, I'd rather go all the way to video/in-person or stick with text. I also prefer to push anything important that isn't extremely small out of instant messaging and to email.
Brainstorming/whiteboarding, 1:1s or performance feedback, team socialization, working through something very difficult (e.g. pair debugging): in-person or video
Incidents, asking for quick help/pointers, small quick questions, social groups, intra-team updates: IM
Bigger design documents and their feedback, trickier questions or debugging that isn't urgent, sharing cool/interesting things, inter-team updates: Email
> do you prefer to do everything via IM, or would you prefer a phone call?
It's hard for me to believe that there are psychopaths among us who prefer call on the phone, slack huddle or even organize meetings instead of just calmly writing messages on IM over coffee.
One advantage is speaking is generally faster than typing. Imagine instead of talking to a bunch of AI you’re talking to a room full of coworkers about the architecture to develop.
If that’s the future, that means a massive reduction in software engineers no? What you are describing would require one technical product manager, not a team of software engineers.
Define everyone. I know a lot of SWEs who don't take their job for granted, always strive to add value, and try to keep skilled constantly and try to be extremely helpful. Maybe in SV where the salaries are high there is some schadenfreude but I don't see that on general for what is a worldwide industry. In most places it's just a standard job.
I don't understand the pleasure of putting people out of work and the pain on people's lives and careers but I guess that's just me.
It seems unlikely that any one individual would be able to output a sufficient amount of context for that to not go off the rails really quickly (or just be extremely inefficient as most agents sit idle waiting for verification of their work)
I can easily see this happening in 2-3 years. Some chat apps already have outstanding voice mode, such as GPT-4o. It's just a matter of integrating that voice mode, and getting the understanding and generated code to be /slightly/ better than it is today.
No. The "golden" end state of coding agents is free and open source coding agents running on my machine (or in whatever machine I want). Can you imagine paying for every command you run in your terminal? For every `ls`, `ps`, `kill`? No sense, right? Well, same for LLMs.
I'm not saying "ban propietary LLMs", I'm saying: hackers (the ones that used to read sites like this) should have as their main tools free and open source ones.
> Can you imagine paying for every command you run in your terminal?
Yes, because hardware and electricity aren't free.
I literally DO pay for every command. I just don't get an itemized bill so there's no transparency about it. Instead, I made some lump-sum hardware payment which is amortized over the total usage I get out of it, plus some marginal increase in my monthly electric bill when I use it.
I agree with the sentiment, but isn’t Claude Code (the CLI) FOSS already? (Not sure it’s coupled to Claude the model API either, but if it is I imagine it’s not too hard to fix.)
Setting aside predictions about the future and what is best for humanity and all that for a moment this is just such a bummer on a personal level. My whole job would become the worst parts of my job.
Aider is definitely in the same camp. Last time I checked, they weren't optimizing for the full "agent infinitely looping until completion" usecase, and didn't have MCP support.
But it's 100% the same class of tool and the awesome part of the unixy model is hopefully agents can be substituted in for each other in your pipeline for whichever one is better for the usecase, just like models are interoperable.
I tried aider today with a Gemini API key and billing account. It’s not close to the experience I have with Claude Code on Saturday which was able to implement a full feature.
The main difference is I interact with Claude Code only through conversation. Aider felt much more like I was talking to two different tools, the model and Aider. For example, constantly having to add files and parse the less than ideal console output compared to how Claude code handles user feedback.
> Cursor, windsurf, etc, are dead ends in that sense as they are local editors, and can not be in CI.
I was doing this with Cursor and MCPs. Got about a full day of this before I was rate limited and dropped to the slowest, dumbest model. I’ve done it with Claude too and quickly exhaust my rate limits. And the PRs are only “good to go” about 25% of the time, and it’s often faster to just do it right than find out where the AI screwed up.
The vision of submitting a feature request and receiving a ready-to-review PR is equally compelling and horrifying from the standpoint of strategy management.
Like Anthropic and most big tech companies, they don't want to show off the best until they need to. They used to stockpile some cool features, and they have time to think about their strategy. But now I feel like they are in a rush to show off everything and I'm worried whether the management has time to think about the big picture.
The moment I am able to outsource work for Jira tickets to a level that AI actually delivers a reasonable pull request, many corporate managers will seriously wonder why keep the offshoring team around.
It seems like the Holy Grail here has become: "A business is one person, the CEO, sitting at his desk doing deals and directing virtual and physical agents to do accounting, run factories, manage R&D, run marketing campaigns, everything." That's it. A single CEO, (maybe) a lawyer, and a big AI/robotics bill = every business. No pesky employees to pay. That's the ultimate end game here, that's what these guys want. Is that what we want?
Of all the professions that are at the risk of being downsized, I think lawyers are up there. We used to consult our lawyers so frequently about things big and small. We have now completely removed the small stuff from that equation. And most of our stuff is small. There is very little of the big stuff and I think LLMs aren't too far from taking care of that as well.
The owner (human) would say "build a company, make me a billion dollars" and that would be the only valuable input needed from him/her. Everything else would be derived & executed by the AI swarm, while owner plays video games (or generally enjoy the product of other people's AI-labor) 100% of the time.
I'd argue GPT4 (2022) was already AGI. It could output anything you (or Tim Cook, or any other smart guy) could possibly output given the relevant context. The reason it doesn't right now is we are not passing in all your life's context. If we achieve this, a human CEO has no edge over an AI CEO.
People are figuring this problem out very quickly, therefore the explosion of agentic capabilities happening right now even though the base model fundamentally does the same stuff as GPT4.
Keep going, the end end goal is that even the customers are AI. And the company doesn't sell anything or do anything, it just trades NFTs and stocks and digital goods. And the money isn't real, it's all crypto. This is the ideal, to create nothing, to sell nothing to no one, and for somehow that to mean you created "value" to society and therefore should be rewarded in material terms. And greatly at that, the people setting all this up expect to be at the tippy top of the social ladder for this "contribution".
This is I guess what happens when you follow capitalism to its logical conclusion. It's exactly what you expect from some reinforcement learning algorithm that only knows how to climb a gradient to maximize a singular reward. The concept of commerce has become the proverbial rat in the skinner box. It has figured out how to mainline the heroin drip if it just holds down the shock button and rewires its brain to get off on the pain. Sure it's an artificial high and hurts like hell to achieve it, but what else is there to live for? We made the line going up mean everything, so that's all that matters now. Doesn't matter if we don't want it, they want it. So that's what it's going to be.
> The "golden" end state of coding agents is that you give it a Feature Request (EG Jira ticket), and it gives you a PR to review and give feedback on.
I see your point but in the other hand how depressing to be left only with the most soul crushing part of software entering - the Jira ticket.
I personally find figuring out what the product should be is the fun part. There still a need for architecting a plan, but the actual act of writing code isn't what gives me personal joy, it's the building of something new.
I understand the craft of code itself is what some people love though!
Thing is, LLMs are already better than people at the "architecting a plan" and "figuring out what the product should be" in details that go beyond high-level vibes. They do that even better than raw coding.
In fact, that's the main reason I like developing quick prototypes and small projects with LLMs. I use them less to write code for me, and more to cut through the bullshit "research" phase of figuring out what code to write, which libraries to pick, what steps and auxiliary work I'm missing in my concept, etc.
Say what you will, but this would have the wonderful side effect of forcing people who write JIRA tickets to actually think through and clearly express what it is they want built.
> The "golden" end state of coding agents is that you give it a Feature Request (EG Jira ticket), and it gives you a PR to review and give feedback on. Cursor, windsurf, etc, are dead ends in that sense as they are local editors, and can not be in CI.
Isn’t that effectively the promise of the most recently released OpenAI codex?
From the reviews I’ve been able to find so far though, quality of output is ehh.
played around with connecting https://github.com/eyaltoledano/claude-task-master via mcp to create a prd which basically replaces the ticket grooming process and then executing it with claude code creating a branch named like the ticket and pushing after having created the unit tests and constant linting.
Claude Code is my favorite way to use LLMs for coding.
However I feel what we really need is to have an open source version of it where you can pass any model and also you can compare different models answers.
(Aider and other alternatives really doesn't feel as good to use as Claude Code)
I know this is not what anthropic would want to do as it removes their moat, but as a consumer I just want the best model and not be tied to an ecosystem. (Which I imagine is the largest fear of LLM model providers)
OpenAI codex is probably the closest to what you're talking about, its open source and you can use models from any provider. It's not as good as claude code right now but I bet it wont take long for them to catch up.
Aider has had support for Python and shell scripting [0] for a long time.
I made a screencast [1] recently that included ad-hoc bash scripting aider as part of the effort to add support for 130 new programming languages. It may give a flavor for how powerful this approach can be.
Freaking love Aider. MCPs are supported soon as well. Testing a development branch. Then you can actually develop end to end using PR, tickets etc using models you trust.
You can disable the automatic commits, but you cannot disable the automatic modification of files. One nice thing about Claude Code is that you can give it feedback on a patch before it is even applied.
Maybe I'm holding it wrong, but I can easily spend $20+ using Claude Code for 2 hours. I've stopped using it because it was too expensive for my personal projects.
Thanks, this is helpful. I tried Claude Code, and thought it had a lot of potential, but I was on track to spend at least $20/day.
For a tool that radically increases productivity (say 2x), I think it could still make sense for a VC funded startup or an established company (even $100/day or $36k/year is still a lot less than hiring another developer). But for a side project or bootstrap effort, $36k/year obviously significantly increases cash expenses. $100/month does not, however.
So, I'm going to go back and upgrade to Max and try it again. If that keeps my costs to $100/month, thats a really different value proposition.
Can you clarify what you mean here? Are you saying I can use Claude Code for a flat rate of $100/month? What are the limits? What if I use more than $100 worth of Code in a month? Their website doesn't seem to make it clear.
Edit:
Found the answer to my own questions
> Send approximately 50-200 prompts with Claude Code every 5 hours[1]
Really tempted to go for this as well. Only wish I could access flat rate Claude through VS Code Cline (or an extension like it) as well - that would be the complete package. $100 / month + ~$$ / day in API credits is gonna get pricey.
I’ve really enjoyed the recent latent space podcasts. I don’t think there is any person†/podcast (or perhaps other content) approaching your general output while maintaining the high SNR. I am continually amazed at the volume and value of public work you’re producing over the last (half?) decade while still growing various businesses. I hope others can find similar productivity gradients. I know you roughly share what works for you but it is not so easy to reproduce.
thanks man, this was nice to read :) idk if it helps but my principles (tm) are here http://learninpublic.org/
i do feel like SNR * quantity could be higher, but its still a challenge to even keep it where it is today. my work life balance/stress levels aren't the best and everyone expects everything from me.
If I was making an AI code assistant, the last thing I would do is to lock it in to a particular foundation model provider.
The only possible way for this to be a successful offering is if we have just now reached a plateau of model effectiveness and all foundation models will now trend towards having almost identical performance and capabilities, with integrators choosing based on small niceties, like having a familiar SDK.
Other than the command/arguments there isn't much locking you in. It's just input/output. Swap it out for something else or simply wrap it. There's not much going on here.
Claude Code could already be used in non-interactive mode, and by extension it could be integrated into other apps in the same manner as any other UNIX command line utility.
This SDK currently supports only command line usage. Isn't that just what we already had?
I don't understand what's actually new here. What am I missing?
> You may not access or use, or help another person to access or use, our Services in the following ways:
> 2. To develop any products or services that compete with our Services, including to develop or train any artificial intelligence or machine learning algorithms or models or resell the Services.
Can somebody please tell me what software product or service doesn’t compete with general intelligence?
Imagine selling intelligence with a legal term that, under strict interpretation, says you’re not allowed to use it for anything.
Is it so vague it’s unenforceable?
How do we own the output if we can’t use it to compete with a general intelligence?
Is it just a “lol nerd no one cares about the legal terms” thing? If no one cares then why would they have a blanket prohibition on using the service ?
We’re supposed to accept liability to lose a lawsuit just to accept their slop? So many questions
When you have model lock in, it’s a big detriment to use because if anyone comes out with SOTA models, and you have already invested infra development on this, you are stuck. Even if you open it up, it’s likely not to work as your model is likely trained specifically on that CLI. Just look at Codex CLI, you can use Gemini 2.5 pro, but it will get randomly stuck or fail a lot vs OpenAI models
I wonder if anyone has done an analysis on the HN user sentiment on the varying AI models over time. I'd be curious to see what that looks like. Increasingly, I'm seeing more and more people talk positively about Gemini and Google (and having used Gemini recently, I align with that sentiment)
I think Bard (lol) and Gemini got a late start and so lots of folks dismissed it but I feel like they've fully caught up. Definitely excited to see what Gemini 3 vs GPT-5 vs Claude 4 looks like!
I'm using Windsurf IDE so have all the main models available. Mainly doing Python, JS, HTML, CSS, some Go. I have found Claude 3.7 outperforms Gemini 2.5 and ChatGPT 4.1, 4o, Deepseek, etc, for my work in most cases.
I suspect that I experience some performance throttling with Gemini 2.5 in my Windsurf setup because it's just not as good as anecdotal reports by others, and benchmarks.
I also seem to run up against a kind of LLM laziness sometimes when they seemingly can't be bothered to answer a challenging prompt ... a consequence of load balancing in action perhaps.
I’ve tried Gemini 2.5 Pro a couple of times and honestly don’t like its output. Claude Sonnet 3.7 is much better at correctly understanding and executing my imprecise prompts.
Gemini 2.5 Flash on the other hand has excellent. I’ve started using it to rewrite whole files after talking the changes through with Claude, because it’s just so ridiculously fast (and dependable enough for applying already outlined changes).
I'm building a browser based tool that runs on your computer, with full tool access of course, that works with all the major models and is far better and more ergonomic to use than code, codex, etc.
If you (or anyone else reading this) wants to try out the upcoming beta give me a ping. (see profile.)
I really like the idea of Claude Code but its rare that I fully spec out a feature on my first request and I can't see how it can be used for frontend features that require a lot of browser-centric iteration/debugging to get right.
You can try my project Plandex[1] to use Gemini in a way that's comparable to Claude Code without copy-pasting. By default, it combines models from the major providers—Anthropic, OpenAI, and Google.
The default planning/coding models are still Sonnet 3.7 for context size under 200k, but you can switch to Gemini with `\set-model gemini-preview`.
Hasn't this been invented already in multiple shapes and forms..? I wrote my own version clai[1] over a year ago which does exactly this, only that it has tools support + is multi vendor.
Honestly though, CLI tools for accessing LLMs (including piping content in and out of them) is such a clearly good idea I'm glad to see more tools implementing the pattern.
What is really needed is a usable multiplexed pipeline management and event system.
Then you can instrument through metaprogramming. For instance, an alert system could be:
"If the threshold goes over 1.0, contact the on-call person through their preferred method" - which may work ... maybe.
Or:
if any( "check_condition {x}", condition_set ):
find_person("on call", right now).contact("preferred")
... the point is to divide everything up into small one-shots, parallelize them, use it as glue/api. Then you get composability. If you can get a framework for coroutines going then it's real game on. The final step is "needs based pulling" which is an inversion of mcp - contextual streams as event based sub-systems.
Things are still too slow for this to be not painful but that won't be the case forever.
Currently everything is linear. Doesn't have to be ... really doesn't.
The "golden" end state of coding agents is that you give it a Feature Request (EG Jira ticket), and it gives you a PR to review and give feedback on. Cursor, windsurf, etc, are dead ends in that sense as they are local editors, and can not be in CI.
If you are tooling your codebase for optimal AI usage (Rules, MCP, etc), you should target a technology that can bridge the gap to headless usage. The fact Claude Code can trivially be used as part of automation through the tools means it's now the default way I thinking about coding agents (Codex, the npm package, is the same).
Disclaimer, I focus on helping companies tool their codebases for optimal agent usage, so I might have a bias here to easily configurable tools.
That's what I want and look forward one day
I hate using voice for anything. I hate getting voice messages, I hate creating them. I get cold sweats just thinking about having to direct 10 AI Agents via voice. Just give me a keyboard and a bunch of screens, thanks.
And don’t get me started on video vs text for learning purely non-physical stuff like programming…
[0]: https://en.wikipedia.org/wiki/Calm_technology
Brainstorming/whiteboarding, 1:1s or performance feedback, team socialization, working through something very difficult (e.g. pair debugging): in-person or video
Incidents, asking for quick help/pointers, small quick questions, social groups, intra-team updates: IM
Bigger design documents and their feedback, trickier questions or debugging that isn't urgent, sharing cool/interesting things, inter-team updates: Email
It's hard for me to believe that there are psychopaths among us who prefer call on the phone, slack huddle or even organize meetings instead of just calmly writing messages on IM over coffee.
sending audio = fast
If the cost of writing software goes down, demand for it will presumably go up...
That's exactly what everyone is hoping for. Well, everyone except software engineers, of course
I don't understand the pleasure of putting people out of work and the pain on people's lives and careers but I guess that's just me.
All those skills can be applied to engineering as well. What makes Fabrice Bellard great? Its not just technical skill I think.
I think some of the most successful people will be a subset of engineers but also Steve Jobs types and artists
I'm not saying "ban propietary LLMs", I'm saying: hackers (the ones that used to read sites like this) should have as their main tools free and open source ones.
Yes, because hardware and electricity aren't free.
I literally DO pay for every command. I just don't get an itemized bill so there's no transparency about it. Instead, I made some lump-sum hardware payment which is amortized over the total usage I get out of it, plus some marginal increase in my monthly electric bill when I use it.
Put the Aider CLI into a GitHub action that's triggered by an issue creation and you're good to go.
But it's 100% the same class of tool and the awesome part of the unixy model is hopefully agents can be substituted in for each other in your pipeline for whichever one is better for the usecase, just like models are interoperable.
The main difference is I interact with Claude Code only through conversation. Aider felt much more like I was talking to two different tools, the model and Aider. For example, constantly having to add files and parse the less than ideal console output compared to how Claude code handles user feedback.
I was doing this with Cursor and MCPs. Got about a full day of this before I was rate limited and dropped to the slowest, dumbest model. I’ve done it with Claude too and quickly exhaust my rate limits. And the PRs are only “good to go” about 25% of the time, and it’s often faster to just do it right than find out where the AI screwed up.
Like Anthropic and most big tech companies, they don't want to show off the best until they need to. They used to stockpile some cool features, and they have time to think about their strategy. But now I feel like they are in a rush to show off everything and I'm worried whether the management has time to think about the big picture.
Of all the professions that are at the risk of being downsized, I think lawyers are up there. We used to consult our lawyers so frequently about things big and small. We have now completely removed the small stuff from that equation. And most of our stuff is small. There is very little of the big stuff and I think LLMs aren't too far from taking care of that as well.
The owner (human) would say "build a company, make me a billion dollars" and that would be the only valuable input needed from him/her. Everything else would be derived & executed by the AI swarm, while owner plays video games (or generally enjoy the product of other people's AI-labor) 100% of the time.
I'd argue GPT4 (2022) was already AGI. It could output anything you (or Tim Cook, or any other smart guy) could possibly output given the relevant context. The reason it doesn't right now is we are not passing in all your life's context. If we achieve this, a human CEO has no edge over an AI CEO.
People are figuring this problem out very quickly, therefore the explosion of agentic capabilities happening right now even though the base model fundamentally does the same stuff as GPT4.
This is I guess what happens when you follow capitalism to its logical conclusion. It's exactly what you expect from some reinforcement learning algorithm that only knows how to climb a gradient to maximize a singular reward. The concept of commerce has become the proverbial rat in the skinner box. It has figured out how to mainline the heroin drip if it just holds down the shock button and rewires its brain to get off on the pain. Sure it's an artificial high and hurts like hell to achieve it, but what else is there to live for? We made the line going up mean everything, so that's all that matters now. Doesn't matter if we don't want it, they want it. So that's what it's going to be.
No, any team.
Management only appears to have power because ownership wants workers to point their ire to them instead of at the real power.
I see your point but in the other hand how depressing to be left only with the most soul crushing part of software entering - the Jira ticket.
I understand the craft of code itself is what some people love though!
In fact, that's the main reason I like developing quick prototypes and small projects with LLMs. I use them less to write code for me, and more to cut through the bullshit "research" phase of figuring out what code to write, which libraries to pick, what steps and auxiliary work I'm missing in my concept, etc.
We will drop the narrow-minded deadweight that can only collect naive requirements, and the coding side that can only implement unambiguous tickets.
Isn’t that effectively the promise of the most recently released OpenAI codex?
From the reviews I’ve been able to find so far though, quality of output is ehh.
I bias a bit to wanting the agent to be a pluggable component into a flow I own, rather than a platform in a box.
It'll be interesting to see where the different value props/use cases of a Delvin/v0 vs a Codex Cloud vs Claude Code/Codex CLI vs Cursor land.
However I feel what we really need is to have an open source version of it where you can pass any model and also you can compare different models answers.
(Aider and other alternatives really doesn't feel as good to use as Claude Code)
I know this is not what anthropic would want to do as it removes their moat, but as a consumer I just want the best model and not be tied to an ecosystem. (Which I imagine is the largest fear of LLM model providers)
https://github.com/openai/codex/tree/main
[0] https://aider.chat/docs/scripting.html
[1] https://aider.chat/docs/recordings/tree-sitter-language-pack...
I don't really want it committing and stuff, i mostly like the UX of Claude Code. Thoughts?
Add a file to your repo and you can talk to any model via issues.
you can skim the transcript but some personal highlights:
- anthropic employees, with unlimited claude, average to $6/day of usage
- headless claude code as a "linux" utility that you use everywhere in CI is pretty compelling
- claude code as a user extensible platform
- future roadmap of claude code: sandboxing, branching, planning
- sonnet 3.7 as a persistent, agentic model
From the link:
"Apparently, there are some engineers inside of Anthropic that have spent >$1,000 in one day!"
The question is what is the P50, P75, and P95 spend per employee?
https://news.ycombinator.com/item?id=43737060
I was listening to this podcast yesterday and I also did a double take when I heard the $6 per day number.
For a tool that radically increases productivity (say 2x), I think it could still make sense for a VC funded startup or an established company (even $100/day or $36k/year is still a lot less than hiring another developer). But for a side project or bootstrap effort, $36k/year obviously significantly increases cash expenses. $100/month does not, however.
So, I'm going to go back and upgrade to Max and try it again. If that keeps my costs to $100/month, thats a really different value proposition.
Edit:
Found the answer to my own questions
> Send approximately 50-200 prompts with Claude Code every 5 hours[1]
Damn. That's a really good deal
[1] https://support.anthropic.com/en/articles/11145838-using-cla...
† simonw, gwern
i do feel like SNR * quantity could be higher, but its still a challenge to even keep it where it is today. my work life balance/stress levels aren't the best and everyone expects everything from me.
The only possible way for this to be a successful offering is if we have just now reached a plateau of model effectiveness and all foundation models will now trend towards having almost identical performance and capabilities, with integrators choosing based on small niceties, like having a familiar SDK.
At this point Claude Code is a software differentiator in the agent coding space.
I am building things related to AI code assistants - we were hacking ways to integrate Claude Code - it was the first thing we wanted to build around.
It's too early to care about lock in.
Need the best, will only build around the best.
This SDK currently supports only command line usage. Isn't that just what we already had?
I don't understand what's actually new here. What am I missing?
Can somebody please tell me what software product or service doesn’t compete with general intelligence?
Imagine selling intelligence with a legal term that, under strict interpretation, says you’re not allowed to use it for anything.
Is it so vague it’s unenforceable?
How do we own the output if we can’t use it to compete with a general intelligence?
Is it just a “lol nerd no one cares about the legal terms” thing? If no one cares then why would they have a blanket prohibition on using the service ?
We’re supposed to accept liability to lose a lawsuit just to accept their slop? So many questions
As it only accepts an API key as far as I can tell.
[0]: https://docs.anthropic.com/en/docs/claude-code/github-action...
I think Bard (lol) and Gemini got a late start and so lots of folks dismissed it but I feel like they've fully caught up. Definitely excited to see what Gemini 3 vs GPT-5 vs Claude 4 looks like!
I suspect that I experience some performance throttling with Gemini 2.5 in my Windsurf setup because it's just not as good as anecdotal reports by others, and benchmarks.
I also seem to run up against a kind of LLM laziness sometimes when they seemingly can't be bothered to answer a challenging prompt ... a consequence of load balancing in action perhaps.
EDIT: Specifically: https://openrouter.ai/rankings/programming?view=week
The two work really well with Gemini as a planner and Claude Code as an executor.
Gemini 2.5 Flash on the other hand has excellent. I’ve started using it to rewrite whole files after talking the changes through with Claude, because it’s just so ridiculously fast (and dependable enough for applying already outlined changes).
If you (or anyone else reading this) wants to try out the upcoming beta give me a ping. (see profile.)
I really like the idea of Claude Code but its rare that I fully spec out a feature on my first request and I can't see how it can be used for frontend features that require a lot of browser-centric iteration/debugging to get right.
The default planning/coding models are still Sonnet 3.7 for context size under 200k, but you can switch to Gemini with `\set-model gemini-preview`.
1 - https://github.com/plandex-ai/plandex
Works for a reasonable chunk of files say 5 to 10 that aren’t too big.
No doubt they’ll get to better file access.
Anyhow I’m quite happy to do the copy and paste because Geminis coding and debugging capability is far better than Claude.
[1]: https://github.com/baalimago/clai
Honestly though, CLI tools for accessing LLMs (including piping content in and out of them) is such a clearly good idea I'm glad to see more tools implementing the pattern.
Then you can instrument through metaprogramming. For instance, an alert system could be:
"If the threshold goes over 1.0, contact the on-call person through their preferred method" - which may work ... maybe.
Or:
if any( "check_condition {x}", condition_set ): find_person("on call", right now).contact("preferred")
... the point is to divide everything up into small one-shots, parallelize them, use it as glue/api. Then you get composability. If you can get a framework for coroutines going then it's real game on. The final step is "needs based pulling" which is an inversion of mcp - contextual streams as event based sub-systems.
Things are still too slow for this to be not painful but that won't be the case forever.
Currently everything is linear. Doesn't have to be ... really doesn't.