OpenCode was the first open source agent I used, and my main workhorse after experimenting briefly with Claude Code and realizing the potential of agentic coding. Due to that, and because it's a popular an open source alternative, I want to be able to recommend it and be enthusiastic about it. The problem for me is that the development practices of the people that are working on it are suboptimal at best; they're constantly releasing at an extremely high cadence, where they don't even spend the time to test or fix things (or even build a proper list of changes for each release), and they add, remove, refine, change, fix, and break features constantly at that accelerated pace.
More than that, it's an extremely large and complex TypeScript code base — probably larger and more complex than it needs to be — and (partly as a result) it's fairly resource inefficient (often uses 1GB of RAM or more. For a TUI).
On top of that, at least I personally find the TUI to be overbearing and a little bit buggy, and the agent to be so full of features that I don't really need — also mildly buggy — that it sort of becomes hard to use and remember how everything is supposed to work and interact.
> and (partly as a result) it's fairly resource inefficient (often uses 1GB of RAM or more. For a TUI).
That's (one of the reasons) why I'm favoring Codex over Claude Code.
Claude Code is an... Electron app (for a TUI? WTH?) and Codex is Rust. The difference is tangible: the former feels sluggish and does some odd redrawing when the terminal size changes, while the latter definitely feels more snappy to me (leaving aside that GPT's responses also seem more concise). At some point, I had both chewing concurrently on the same machine and same project, and Claude Code was using multiple GBs of RAM and 100% CPU whereas Codex was happy with 80 MB and 6%.
Performance _is_ a feature and I'm afraid the amounts of code AI produces without supervision lead to an amount of bloat we haven't seen before...
I think you’re confusing capital c Claude Code, the desktop Electron app, and lowercase c `claude`, the command line tool with an interactive TUI. They’re both TypeScript under the hood, but the latter is React + Ink rendered into the terminal.
The redraw glitches you’re referring to are actually signs of what I consider to be a pretty major feature, a reason to use `claude` instead of `codex` or `opencode`: `claude` doesn’t use the alternate screen, whereas the other two do. Meaning that it uses the standard screen buffer, meaning that your chat history is in the terminal (or multiplexer) scrollback. I much prefer that, and I totally get why they’ve put so much effort into getting it to work well.
In that context handling SIGWINCH has some issues and trickiness. Well worth the tradeoff, imo.
agents don't really care and they're doing anywhere between 90-100% of the work on CC. if anything, rust is better as it has more built-in verification out of the box.
I am more concerned about their, umm, gallant approach to security. Not only that OpenCode is permissive by default in what it is allowed to do, but that it apparently tries to pull its config from the web (provider-based URL) by default [1]. There is also this open GitHub issue [2], which I find quite concerning (worst case, it's an RCE vulnerability).
It also sends all of your prompts to Grok's free tier by default, and the free tier trains on your submitted information, X AI can do whatever they want with that, including building ad profiles, etc.
You need to set an explicit "small model" in OpenCode to disable that.
The small_model option configures a separate model for lightweight tasks like title generation. By default, OpenCode tries to use a cheaper model if one is available from your provider, otherwise it falls back to your main model.
I would expect that if you set a local model it would just use the same model. Or if for example you set GPT as main model, it would use something else from OpenAI. I see no mentions of Grok as default
This. I work on projects that warrant a self hosted model to ensure nothing is leaked to the cloud. Imagine my surprise when I discovered that even though the only configured model is local, all my prompts are sent to the cloud to... generate a session title. Fortunately caught during testing phase.
I’m curious if there’s a reason you’re not just coding in a container without access to the internet, or some similar setup? If I was worried about things in my dev chain accessing any cloud service, I’d be worried about IDE plugins, libraries included in imports, etc. and probably not want internet access at all.
They're talking about before it's configured by the user. It defaults to 'free' models so that the user can ask a question immediately on startup. Once you configure a provider, the default models aren't used.
No, it is still configurable. You can specify in your opencode.json config that it should be able to run everything. I think they just argued that it shouldn't be the default. Which I agree with.
> The problem for me is that the development practices of the people that are working on it are suboptimal at best; they're constantly releasing at an extremely high cadence, where they don't even spend the time to test or fix things (or even build a proper list of changes for each release), and they add, remove, refine, change, fix, and break features constantly at that accelerated pace.
this is what i notice with openclaw as well. there have been releases where they break production features. unfortunately this is what happens when code becomes a commidity, everyone thinks that shipping fast is the moat but at the expense of suboptimality since they know a fix can be implemented quickly on the next release.
Openclaw has 20k commits, almost 700k lines of code, and it is only four months old. I feel confident that that sort of code base would have a no coherent architecture at all, and also that no human has a good mental model of how the various subsystems interact.
I’m sure we’ll all learn a lot from these early days of agentic coding.
> I’m sure we’ll all learn a lot from these early days of agentic coding.
So far what I am learning (from watching all of this) is that our constant claims that quality and security matter seem to not be true on average. Depressingly.
I think what we're seeing is a phase transition. In the early days of any paradigm shift, velocity trumps stability because the market rewards first movers.
But as agents move from prototypes to production, the calculus changes. Production systems need:
- Memory continuity across sessions
- Predictable behavior across updates
- Security boundaries that don't leak
The tools that prioritize these will win the enterprise market. The ones that don't will stay in the prototype/hobbyist space.
We're still in the "move fast" phase, but the "break things" part is starting to hurt real users. The pendulum will swing back.
This makes sense. Development velocity is bought by having a short product life with few users. As you gain users that depend on your product, velocity must drop by definition.
The reason for this is that product development involves making decisions which can later be classified as good or bad decisions.
The good decisions must remain stable, while the bad decisions must remain open to change and therefore remain unstable.
The AI doesn't know anything about the user experience, which means it will inevitably change the good decisions as well.
> So far what I am learning (from watching all of this) is that our constant claims that quality and security matter seem to not be true on average.
Only for the non-pro users. After all, those users were happy to use excel to write the programs.
What we're seeing now is that more and more developers find they are happy with even less determinism than the Excel process.
Maybe they're right; maybe software doesn't need any coherence, stability, security or even correctness. Maybe the class of software they produce doesn't need those things.
20 for me, and let's not exaggerate. We've given lip service to it this entire time. Hell look at any of the corps we're talking about (including where I work) and they're demanding "velocity without lowering the quality bar", but it's a lie: they don't care about the quality bar in the slightest.
I’m learning that projects, developed with the help of agents, even when developers claim that they review and steer everything, ultimately are not fully understood or owned by the developers, and very soon turns into a thousand reinvented wheels strapped together by tape.
> very soon turns into a thousand reinvented wheels strapped together by tape.
Also most of the long running enterprise projects I’ve seen - there was one that had been around for like 10 years and like about 75% of the devs I hadn’t even heard of and none of the original ones were in the project at all.
The thing had no less than three auditing mechanisms, three ways of interacting with the database, mixed naming conventions, like two validation mechanisms none of which were what Spring recommended and also configurations versioned for app servers that weren’t even in use.
This was all before AI, it’s not like you need it for projects to turn into slop and AI slop isn’t that much different from human slop (none of them gave a shit about ADRs or proper docs on why things are done a certain way, though Wiki had some fossilized meeting notes with nothing actually useful) except that AI can produce this stuff more quickly.
When encountered, I just relied on writing tests and reworking the older slop with something newer (with better AI models and tooling) and the overall quality improved.
We're still in the very early days of generative AI, and people and markets are already prioritizing quality over quantity. Quantity is irrelevant when it comes value.
All code is not fungible, "irreverent code that kinda looks okay at first glance" might be a commodity, but well-tested, well-designed and well-understood code is what's valuable.
and once you've got your wish: ugly code without tests or a way to comprehend it, but cheap!
How much value are you going to be able to extract over its lifetime once your customers want to see some additional features or improvements?
How much expensive maintenance burden are you incurring once any change (human or LLM generated) is likely to introduce bugs you have no better way of identifying than shipping to your paying customers?
Maybe LLM+tooling is going to get there with producing a comprehensible and well tested system but my anectodal experience is not promising. I find that AI is great until you hit its limit on a topic and then it will merrily generate tokens in a loop suggesting the same won't-work-fix forever.
What you wrote aligns with my experience so far.
It's fast and easy to get something working, but in a number of cases it (Opus) just gets stuck 'spinning' and no number of prompts is going to fix that.
Moreover - when creating things from scratch it tends to use average/insecure/ inefficient approaches that later take a lot of time to fix.
The whole thing reminds me a bit of the many RAD tools that were supposed to 'solve' programming. While it was easy to start and produce something with those tools, at some point you started spending way too much time working around the limitations and wished you started from scratch without it.
I would think that the better the code is designed and factored and refactored, the easier it is to maintain and evolve, detect and remove bugs and security vulnerabilties from it. The ease of maintenance helps both AI and humans.
There are limits to what even AI can do to code, within practical time-limits. Using AI also costs money. So, easier it is to maintain and evolve a piece of software, the cheaper it will be to the owners of that application.
I'm of the opinion that the diligence of experts is part of what makes code valuable assets, and that the market does an alright job of eventually differentiating between reliable products/brands and operations that are just winging it with AI[1].
Claude Code breaks production features and doesn't say anything about it. The product has just shifted gears with little to no ceremony.
I expect that from something guiding the market, but there have been times where stuff changes, and it isn't even clear if it is a bug or a permanent decision. I suspect they don't even know.
It's understandable and even desirable that a new piece of code rapidly evolves as they iterate and fix bugs. I'd only be concerned if they keep this pattern for too long. In the early phases, I like keeping up with all the cutting edge developments. Projects where dev get afraid to ship because of breaking things end up becoming bloated with unnecessary backward compatibility.
Is there a name for these types of "overbearing" and visually busy "TUIs"? It seems like all the other agents have the same aesthetic and it is unlike traditional nurses or plain text interfaces in a bad way IMO. The constant spinners, sidebars and needless margins are a nuisance to me. Especially over an ssh connection in a tmux session it feels wrong.
I recently listened to this episode from the Claude Code creator (here is the video version: https://www.youtube.com/watch?v=PQU9o_5rHC4) and it sounded like their development process was somewhat similar - he said something like their entire codebase has 100% churn every 6 months. But I would assume they have a more professional software delivery process.
I would (incorrectly) assume that a product like this would be heavily tested via AI - why not? AI should be writing all the code, so why would the humans not invest in and require extreme levels of testing since AI is really good at that?
I feel like our industry goes through these phases where there's an obvious thought leader that everyone's copying because they are revolutionary.
Like Rails/DHH was one phase, Git/GitHub another.
And right now it's kinda Claude Code. But they're so obviously really bad at development that it feels like a MLM scam.
I'm just describing the feeling I'm getting, perhaps badly. I use Claude, I recommended Claude for the company I worked at. But by god they're bloody awful at development.
It feels like the point where someone else steps in with a rock solid, dependable, competitor and then everyone forgets Claude Code ever existed.
I mean, I'm slowly trying to learn lightweight formal methods (i.e. what stuff like Alloy or Quint do), behavior driven development, more advanced testing systems for UIs, red-green TDD, etc, which I never bothered to learn as much before, precisely because they can handle the boilerplate aspects of these things, so I can focus on specifying the core features or properties I need for the system, or thinking through the behavior, information flow, and architecture of the system, and it can translate that into machine-verifiable stuff, so that my code is more reliable! I'm very early on that path, though. It's hard!
I heard from somebody inside Anthropic that it's really two companies, one which are using AI for everything and the other which spends all their time putting out fires.
OpenCode's creator acknowledged that the ease of shipping has let them ship prototype features that probably weren't worth shipping and that they need to invest more time cleaning up and fixing things.
Uff. This is exactly what Casey Muratori and his friend was talking about in of their more recent podcast. Features that would never get implemented because of time constraints now do thanks to LLMs and now they have a huge codebase to maintain
I'm still trying to figure out how "open" it really is; There are reports that it phones home a lot[0], and there is even a fork that claims to remove this behavior[1]:
I think there’s a conflict between “open” as in “open source”, and “open” as in “open about the practice” paired with the fact we usually don’t review software’s source scrupulously enough to spot unwanted behaviors”.
so how is telemetry not open? If you don't like telemetry for dogmatic reasons then don't use it. Find the alternative magical product whose dev team is able to improve the software blindfolded
> Find the alternative magical product whose dev team is able to improve the software blindfolded
The choice isn't "telemetry or you're blindfolded", the other options include actually interacting with your userbase. Surveys exist, interviews exist, focus groups exist, fostering communities that you can engage is a thing, etc.
For example, I was recruited and paid $500 to spend an hour on a panel discussing what developers want out of platforms like DigitalOcean, what we don't like, where our pain points are. I put the dollar amount there only to emphasize how valuable such information is from one user. You don't get that kind of information from telemetry.
> Surveys exist, interviews exist, focus groups exist, fostering communities that you can engage is a thing, etc.
We all know it’s extremely, extremely hard to interact with your userbase.
> For example I was paid $500 an hour
+the time to find volunteers doubled that, so for $1000 an hour x 10 user interviews, a free software can have feedback from 0.001% of their users. I dislike telemetry, but it’s a lie to say it’s optional.
—a company with no telemetry on neither of our downloadable or cloud product.
> We all know it’s extremely, extremely hard to interact with your userbase.
On the contrary, your users will tell you what you need to know, you just have to pay attention.
> I dislike telemetry, but it’s a lie to say it’s optional.
The lie is believing it’s necessary. Software was successful before telemetry was a thing, and tools without telemetry continue to be successful. Plenty of independent developers ship zero telemetry in their products and continue to be successful.
Probably all describe problems stem from the developers using agent coding; including using TypeScript, since these tools are usually more familiar with Js/Js adjacent web development languages.
Perhaps the use of coding agents may have encouraged this behavior, but it is perfectly possible to do the opposite with agents as well — for instance, to use agents to make it easier to set up and maintain a good testing scaffold for TUI stuff, a comprehensive test suite top to bottom, in a way maintainers may not have had the time/energy/interest to do before, or to rewrite in a faster and more resource efficient language that you may find more verbose, be less familiar with, or find annoying to write — and nothing is forcing them to release as often as they are, instead of just having a high commit velocity. I've personally found AIs to be just as good at Go or Rust as TypeScript, perhaps better, as well, so I don't think there was anything forcing them to go with TypeScript. I think they're just somewhat irresponsible devs.
The value of having (and executing) a coherent product vision is extremely undervalued in FOSS, and IMO the difference between a successful project in the long-term and the kind of sploogeware that just snowballs with low-value features.
> The value of having (and executing) a coherent product vision is extremely undervalued in FOSS
Interesting you say this because I'd say the opposite is true historically, especially in the systems software community and among older folks. "Do one thing and do it well" seems to be the prevailing mindset behind many foundational tools. I think this why so many are/were irked by systemd. On the other hand newer tools that are more heavily marketed and often have some commercial angle seem to be in a perpetual state of tacking on new features in lieu of refining their raison d'etre.
You must never rely on AI itself for authorization… don’t let it run on an environment where it can do that. I can’t believe this needs to be said but everyone seems to have lost their mind and decided to give all their permissions away to a non deterministic thing that when prompted correctly will send it all out to whoever asks it nicely.
I’ve been testing opencode and it feels TUI in appearance only. I prefer commandline and TUIs and in my mind TUI idea is to be low level, extremely portable interface and to get out of the way. Opencode does not have low color, standard terminal theme so had to switch to a proper terminal program. Copy paste is hijacked so I need to write code out to file in order to get a snippet. The enter key (as in the return by the keypad) does not work for sending a line. I have not tested but don’t think this would work over SSH even. I have been googling around to find if I am holding it wrong but it feels to break expectations of a terminal app in a way that I wish they would have made it a gui. Makes me sad because I think the goods are there and it’s otherwise good.
I don’t think good TUI’s are the same as good command line programs. Great tui apps would to me be things like Norton/midnight commander, borlands turbo pascal, vim, eMacs and things like that
Yes cli and tui are not the same, but I expect TUI to work decent in general terminal emulator and not acitvely block copying and pasting. Having to install supported terminal emulator goes against the vibe.
I’m a little surprised by your description of constant releases and instability. That matches how I would describe Claude Code, and has been one of the main reasons I tend to use OpenCode more than Claude Code.
OpenCode has been much more stable for me in the 6 months or so that I’ve been comparing the two in earnest.
I use Droid specifically because Claude Code breaks too often for me. And then Droid broke too (but rarely), and I just stuck to not upgrading (like I don't upgrade WebStorm. Dev tools are so fragile)
That is very disappointing coz I've been wanting to try an alternative to Gemini CLI for exactly these reasons. The AI is great but the actual software is a buggy, slow, bloated blob of TypeScript (on a custom Node runtime IIUC!) that I really hate running. It takes multiple seconds to start, requires restarting to apply settings, constantly fucks up the terminal, often crashes due to JS heap overflows, doesn't respect my home dir (~/.gemini? Come on folks are we serious?), has an utterly unusable permission system, etc etc. Yet they had plenty of energy to inject silly terminal graphics and have dumb jokes and tips scroll across the screen.
Is Claude Code like this too? I wonder if Pi is any better.
A big downside would be paying actual cost price for tokens but on the other hand, I wouldn't be tied to Google's model backend which is also extremely flaky and unable to meet demand a lot of the time. If I could get real work done with open models (no idea if that's the case yet) and switch providers when a given provider falls over, that would be great.
Yeah every time I want to like it, scrolling is glitched vs codex and Claude. And other various things like: why is this giant model list hard coded for ollama or other local methods vs loading what I actually have...
On top of that. Open code go was a complete scam. It was not advertised as having lower quality models when I paid and glm5 was broken vs another provider, returning gibberish and very dumb on the same prompt
The biggest reason is I don't like being locked into an ecosystem. I can use whatever I want with OpenCode, not so much with Codex and Claude Code. Right now I'm only using GPT with it, but I like the option.
CC I have the least experience with. It just seemed buggy and unpolished to me. Codex was fine, but there was something about it that just didn't feel right. It seemed fined for code tasks but just as often I want to do research or discuss the code base, and for whatever reason I seemed to get terse less useful answers using Codex even when it's backed by the same model.
OpenCode works well, I haven't had any issues with bugs or things breaking, and it just felt comfortable to use right from the jump.
> they're constantly releasing at an extremely high cadence, where they don't even spend the time to test or fix things
Tbf, this seems exactly like Claude Code, they are releasing about one new version per day, sometimes even multiple per day. It’s a bit annoying constantly getting those messages saying to upgrade cc to the latest version
Yeah I tried using it when oh-my-opencode (now oh-my-openagent) started popping off and found it had highly unstable. I just stick with internal tooling now.
I tried it briefly and the practice - argued for strategy for operation actually - to override my working folder seelction and altering to the parent root git folder is a no go.
For serious coding work I use the Zed Agent; for everything else I use pi with a few skills. Overall, though, I'd recommend Pi plus a few extensions for any features you miss extremely highly. It's also TypeScript, but doesn't suffer from the other problems OC has IME. It's a beautiful little program.
Big +1 to Pi[1]. The simplicity makes it really easy to extend yourself too, so at this point I have a pretty nice little setup that's very specific to my personal workflows. The monorepo for the project also has other nice utilities like a solid agent SDK. I also use other tools like Claude Code for "serious" work, but I do find myself reaching for Pi more consistently as I've gotten more confident with my setup.
I've been building VT Code (https://github.com/vinhnx/vtcode), a Rust-based semantic coding agent. Just landed Codex OAuth with PKCE exchange, credentials go into the system keyring.
I build VT Code with Tree-sitter for semantic understanding and OS-native sandboxing. It's still early but I confident it usable. I hope you'll give it a try.
I tried running Opencode on my 7$/yr 512mb vps but it had the OOM issue and yes it needs 1GB of ram or more.
I then tried running other options like picoclaw/picocode etc but they were all really hard to manage/create
The UI/UX I want is that I can just put my free openrouter api key in and then I am ready to go to get access to free models like Arcee AI right now
After reading your comments/I read this thread, I tried crush by charmbracelet again and it gives the UI/UX that I want.
I am definitely impressed by crush/ the charm team. They are on HN and they work great for me, highly recommended if you want something which can work on low constrained devices
I do feel like Charm's TUI's are too beautiful in the sense that running a connection over SSH can delay so when I tried to copy some things, the delay made things less copy-able but overall, I think that I am using Crush and I am happy for the most part :-)
Edit: That being said, just as I was typing this, Crush took all the Free requests from Openrouter that I get for free so it might be a bit of minor issue but overall its not much of an issue from Crush side, so still overall, my point is that Crush is worth checking out
Kudos to the CharmBracelet team for making awesome golang applications!
Isn't this pretty much the standard across projects that make heavy use of AI code generation?
Using AI to generate all your code only really makes sense if you prioritize shipping features as fast as possible over the quality, stability and efficiency of the code, because that's the only case in which the actual act of writing code is the bottleneck.
I don't think that's true at all. As I said, in a response to another person blaming it on agentic coding above, there are a very large number of ways to use coding agents to make your programs faster, more efficient, more reliable, and more refined that also benefit from agents making the code writing research, data piping, and refactoring process quicker and less exhausting. For instance, by helping you set up testing scaffolding, handling the boilerplate around tests while you specify some example features or properties you want to test and expands them, rewriting into a more efficient language, large-scale refactors to use better data structures or architectures, or allowing you to use a more efficient or reliable language that you don't know as well or find to have too much boilerplate or compiler annoyance to otherwise deal with yourself. Then there are sort of higher level more phenomenological or subjective benefits, such as helping you focus on the system architecture and data flow, and only zoom in on particular algorithms or areas of the code base that are specifically relevant, instead of forever getting lost in the weeds of thinking about specific syntax and compiler errors or looking up a bunch of API documentation that isn't super important for the core of what you're trying to do and so on.
Personally, I find this idea that "coding isn't the bottleneck" completely preposterous. Getting all of the API documentation, the syntax, organizing and typing out all of the text, finding the correct places in the code base and understanding the code base in general, dealing with silly compiler errors and type errors, writing a ton of error handling, dealing with the inevitable and inoraticable boilerplate of programming (unless you're one of those people that believe macros are actually a good idea and would meaningfully solve this), all are a regular and substantial occurrence, even if you aren't writing thousands of lines of code a day. And you need to write code in order to be able to get a sense for the limitations of the technology you're using and the shape of the problem you're dealing with in order to then come up with and iterate on a better architecture or approach to the problem. And you need to see your program running in order to evaluate whether it's functionality and design a satisfactory and then to iterate on that. So coding is actually the upfront costs that you need to pay in order to and even start properly thinking about a problem. So being able to get a prototype out quickly is very important. Also, I find it hard to believe that you've never been in a situation where you wanted to make a simple change or refactor that would have resulted in needing to update 15 different call sites to do properly in a way that was just slightly variable enough or complex enough that editor macros or IDE refactoring capabilities wouldn't be capable of.
That's not to mention the fact that if agentic coding can make deploying faster, then it can also make deploying the same amount at the same cadence easier and more relaxing.
You're both right. AI can be used to do either fast releases or well designed code. Don't say both, as you're not making time, you're moving time between those two.
Which one you think companies prefer? Or if you're a consulting business, which one do you think your clients prefer?
> AI can be used to do either fast releases or well designed code
I have yet to actually see a single example of the latter, though. OpenCode isn't an isolated case - every project with heavy AI involvement that I've personally examined or used suffers from serious architectural issues, tons of obvious bugs and quirks, or both. And these are mostly independent open source projects, where corporate interests are (hopefully) not an influence.
I will continue to believe it's not actually possible until I am proven wrong with concrete examples. The incentives just aren't there. It's easy to say "just mindlessly follow X principle and your software will be good", where X is usually some variation of "just add more tests", "just add more agents", "just spend more time planning" etc. but I choose to believe that good software cannot be created without the involvement of someone who has a passion for writing good software - someone who wouldn't want to let an LLM do the job for them in the first place.
> It's easy to say "just mindlessly follow X principle and your software will be good", where X is usually some variation of "just add more tests", "just add more agents", "just spend more time planning" etc
That's a complete strawman of what I — or others trying to learn how to use coding agents to increase quality, like Simon Willison or the Oxide team — am saying.
> but I choose to believe that good software cannot be created without the involvement of someone who has a passion for writing good software - someone who wouldn't want to let an LLM do the job for them in the first place.
This is just a no true Scotsman. I prefer to use coding agents because they don't forget details, or get exhausted, or overwhelmed, or lazy, or give up, ever — whereas I might. Therefore, they allow me to do all of the things that improve code and software quality more extensively and thoroughly, like refactors, performance improvements, and tests among other things (because yes, there is no single panacea). Furthermore, I do still care about the clarity, concision, modularity, referential transparency, separation of concerns, local reasonability, cognitive load, and other good qualities of the code, because if those aren't kept up a) I can't review the code effectively or debug things as easily when they go wrong, b) the agent itself will struggle to male changes without breaking other things, and struggle to debug, c) those things often eventually effect the quality of the end state software.
Additionally, what you say is empirically false. Many people who do deeply value quality software and code quality, such as the creators of Flask, Redis, and SerenityOS/Ladybird, all use and value agentic coding.
Just because you haven't seen good quality software with a large amount of agentic influence doesn't mean it isn't possible. That's very close minded.
I found out about OpenCode through the Anthropic feud. I now spend most of my AI time in it, both at work and at home. It turns out to be pretty great for general chat too, with the ability to easily integrate various tools you might need (search being the top one of course).
I have things to criticize about it, their approach to security and pulling in code being my main one, but over all it’s the most complete solution I’ve found.
They have a server/client architecture, a client SDK, a pretty good web UI and use pretty standard technologies.
The extensibility story is good and just seems like the right paradigms mostly, with agents, skills, plugins and providers.
They also ship very fast, both for good and bad, I’ve personally enjoyed the rapid improvements (~2 days from criticizing not being able to disable the default provider in the web ui to being able to).
I think OpenCode has a pretty bright future and so far I think that my issues with it should be pretty fixable. The amount of tasteful choices they’ve made dwarfs the few untasteful ones for me so far.
More importantly, the current dev branch source for packages/opencode/src/session/summary.ts shows summarizeMessage() now only computes diffs and updates the message summary object; it does not make an LLM call there anymore. The current code path calls summarizeSession() and summarizeMessage(), and summarizeMessage() just filters messages, computes diffs, sets userMsg.summary.diffs, and saves the message.
Yikes... sending prompts to a third party by default with no disclosure in the setup flow is a rough look for a tool that positions itself as the open sources alternative. "Open" loses meaning fast if the defaults work against the user.
Geez there should be a big warning on the tin about this. They’re so neatly integrated with copilot that I assumed (and told others) that they had all the privacy guarantees of copilot :(
Also, even when using local models in ollama or lmstudio, prompts are proxied via their domain, so never put anything sensitive even when using local setup
To be clear, that seems to be about the webui only, the TUI doesn't seem affected. I haven't fully investigated this myself, but when I run opencode (1.2.27-a6ef9e9-dirty) + mitmproxy and using LM Studio as the backend, when starting opencode + executing a prompt, I only see two requests, both to my LM Studio instance, both normal inference requests (one for the chat itself + one for generating the title).
Everything you read on the internet seems exaggerated today. Especially true for reddit, and especially especially true for r/LocalLllama which is a former shadow of itself. Today it's mostly sockpuppets pushing various tools and models, and other sockpuppets trying to push misinformation about their competitors tools/models.
Are you using Grok for the coding? Because I have Copilot connected and I can see the request to Copilot for the summaries - with no "small model" setting even visible in my settings.
To the provider you select in the UI, I agree. But OpenCode automatically sends prompts to their free "Zen" proxy, even without choosing it in the UI.
Imagine someone using it at work, where they are only allowed to use a GitHub Copilot Business subscription (which is supported in OpenCode). Now they have sent proprietary code to a third party, and don't even know they're doing it.
This is exactly me considering what I might have leaked to god knows who via grok. I was hyped by opencode but now I’m thinking of alternatives. A huge red flag… at best irresponsible?
The team also is not breathlessly talking about how coding is dead. They have pretty sane takes on AI coding including trying to help people who care about code quality.
The Agent that is blacklisted from Anthropic AI, soon more to come.
I really like how their subagents work, as a bonus I get to choose which model is in which agent. Sadly I have to resort to the mess that Anthropic calls Claude Code
They are not blacklisted. You are allowed to use the API at commercial usage pricing. You are just not allowed to use your Claude Code subscription with OpenCode (or any other third‑party harness for the record).
If you're not paying full-fat API prices, then probably.
From what I've heard, the metrics used by Anthropic to detect unauthorized clients is pretty easy to sidestep if you look at the existing solutions out there. Better than getting your account banned.
With Anthropic, you either pay per token with an API key (expensive), or use their subscription, but only with the tools that they provide you - Claude, Claude Cowork and Claude Code (both GUI and CLI variants). Individuals generally get to use the subscriptions, companies, especially the ones building services on top of their models, are expected to pay per token. Same applies to various third party tools.
The belief is that the subscriptions are subsidized by them (or just heavily cut into profit margins) so for whatever reason they're trying to maintain control over the harness - maybe to gather more usage analytics and gain an edge over competitors and improve their models better to work with it, or perhaps to route certain requests to Haiku or Sonnet instead of using Opus for everything, to cut down on the compute.
Given the ample usage limits, I personally just use Claude Code now with their 100 USD per month subscription because it gives me the best value - kind of sucks that they won't support other harnesses though (especially custom GUIs for managing parallel tasks/projects). OpenCode never worked well for me on Windows though, also used Codex and Gemini CLI.
>or perhaps to route certain requests to Haiku or Sonnet instead of using Opus for everything, to cut down on the compute
You can point Claude Code at a local inference server (e.g. llama.cpp, vLLM) and see which model names it sends each request to. It's not hard to do a MITM against it either. Claude Code does send some requests to Haiku, but not the ones you're making with whatever model you have it set to - these are tool result processing requests, conversation summary / title generation requests, etc - low complexity background stuff.
Now, Anthropic could simply take requests to their Opus model and internally route them to Sonnet on the server side, but then it wouldn't really matter which harness was used or what the client requests anyway, as this would be happening server-side.
Sounds pretty sane, the same way how OpenWebUI and probably other software out there also has a concept of “tool models”, something you use for all the lower priority stuff.
Actually curious to hear what others think about why Anthropic is so set on disallowing 3rd party tools on subscriptions.
The sota models are largely undifferentiated from each other in performance right now. And it’s possible open weight models will get “good enough” relatively soonish. This creates a classic case where inference becomes a commodity. Commodities have very low margins. Training puts them in an economic hole where low margins will kill them.
So they have to move up the stack to higher margin business solutions. Which is why they offer subsidized subscription plans in the first place. It’s a marketing cost. But they want those marketing dollars to drive up the stack not commodity inference use cases.
Anthropic's model deployments for Claude Code are likely optimized for Claude Code. I wouldn't be surprised if they had optimizations like sharing of system prompt KV-cache across users, or a speculative execution model specifically fine-tuned for the way Claude Code does tool calls.
When setting your token limits, their economics calculations likely assume that those optimizations are going to work. If you're using a different agent, you're basically underpaying for your tokens.
It’s probably a mixture of things including direct control over how the api is called and used as pointed out above and giving a discount for using their ecosystem. They are in fact a business so it should not surprise anyone they act as one.
It might well be a mixture, but 95% of that mixture is vendor lock in. Same reason they don't support AGENTS.md, they want to add friction in switching.
It's very straightforward to instrument CC under tmux with send-keys and capturep. You could easily use that for distillation, IMO. There are also detailed I/O logs.
Anthropic has an API, you can use any client but they charge per input/output/cache token.
One-price-per-month subscriptions (Claude Code Pro/MAX @ $20/$100/$200 a month) use a different authentication mechanism, OAUTH. The useful difference is you get a lot more inference than you can for the same cost using the API but they require you to use Claude Code as a client.
Some clients have made it simple to use your subscription key with them and they are getting cease and desist letters.
The highest in in the industry for API pricing right now is GPT-5.4-Pro, OpenRouter adding that as an option in their Auto Router was when I had to go customise the routing settings because it was not even close to providing $30/m input tokens and $180/m output tokens of value (for context Opus 4.6 is $5/m input and $25/m output)
(Ok, technically o1-pro is even more expensive, but I'm assuming that's a "please move on" pricing)
Sometimes people want to be real pedants about licensing terms when it comes to OSS, assuming such terms are completely bulletproof, other times people don't think the terms of their agreement with a service provider should have any force at all.
I pay $100/mo to Anthropic. Yesterday I coded one small feature via an API key by accident and it cost $6. At this rate, it will cost me $1000/mo to develop with Opus. I might as well code by hand, or switch to the $20 Codex plan, which will probably be more than enough.
I'd rather switch to OpenAI than give up my favorite harness.
My monthly "connection fee" is more than that (no solar, just EV). Your cartel needs to step it up!
For me it's $0.8/kWh during peak, $0.47 off peak, and super off peak of $0.15. I accidentally left a little mini 500W heater on all day, while I was out, costing > 5% of your whole month!
Yeah I had a similar experience one time. Which is why I laugh when people suggest Anthropic is profitable. Sure, maybe if everyone does API pricing. Which they won’t because it’s so damn expensive. Another way to think about it is API pricing is a glimpse into the future when everyone is dependent on these services and the subscription model price increases start.
IMO, OpenAI have either implicitly committed to becoming the IT service for Trump's secret police, or they've willingly signed up for the harsh retaliation Anthropic's getting, knowing that the Trump administration will inevitably try to push OpenAI around in the same way, if they meaningfully refuse to assist in domestic mass surveillance efforts.
probably more agents to be blocked by anthropic. i've seen theo from t3.gg go through a bunch of loopholes to support claude in his t3code app just so anthropic doesn't sue their asses.
There are boards starting in the $1500-$2000 range, and complete systems in the $2500-$2700 range. I actually don't know of any Strix Halo mini PCs that cost $3000, do you?
EDIT: The system I bought last summer for $1980 and just took delivery of in October, Beelink GTR 9 Pro, is now $2999.... wow...
I love OpenCode! I wrote a plugin that adds two tools: prune and retrieve. Prune lets the LLM select messages to remove from the conversation and replace with a summary and key terms. The retrieve tool lets it get those original messages back in case they're needed. I've been livestreaming the development and using it on side projects to make sure it's actually effective... And it turns out it really is! It feels like working with an infinite context window.
Long tool outputs/command outputs everything in my harness is spilled over to the filesystem. Context messages are truncated and split to filesystem with a breadcrumb for retrieving the full message.
Assuming you pay per token, which seems like a really strange workflow to lock yourself into at this point. Neither paid monthly plans nor local models suffer from that issue.
I tried once to use APIs for agents but seeing a counter of money go up and eventually landing at like $20 for one change, made it really hard to justify. I'd rather pay $200/month before I'd be OK with that sort of experience.
Pi is refreshingly minimal in terms of system prompts, but still works really well and that makes me wonder whether other harnesses are overdoing. Look at OpenCode's prompts, for instance - long, mostly based on feels and IMO unnecessary. I would've liked to just overwrite OC's system prompts with Pi's (to get other features that Pi doesn't have) but that isn't possible today (without maintaining a custom fork)
JS is not something that was developed with CLI in mind and on top of that that language does not lend itself to be good for LLM generation as it has pretty weak validation compared to e.g. Rust, or event C, even python.
It’s simply one of the most productive languages. It actually has a very strong type system, while still being a dynamic language that doesn’t have to be compiled, leading to very fast iteration. It’s also THE language you use when writing UIs. Execution is actually pretty fast through the runtimes we have available nowadays.
The only other interpreted language is Python and that thoroughly feels like a toy in comparison (typing situation still very much in progress, very weak ORM situation, not even a usable package manger until recently!).
In pi’s case there is a plugin system. It’s much easier to make a self extending agent work with Python or JavaScript than most other languages. JavaScript has the benefit that it has a great typing system on top with TypeScript.
For a TUI agent, runtime performance is not the bottleneck, not by far. Hackability is the USP. Pi has extensions hotreloading which comes almost for free with jiti. The fact that the source is the shipped artifact (unlike Go/Rust) also helps the agent seeing its own code and the ability to write and load its own extensions based on that. A fact that OpenClaw’s success is in part based on IMO.
I can’t find the tweet from Mario (the author), but he prefers the Typescript/npm ecosystem for non-performance critical systems because it hits a sweet spot for him. I admire his work and he’s a real polyglot, so I tend to think he has done his homework. You’ll find pi memory usage quite low btw.
OK, make sense, but there are also claw clones that are in Rust (and self modifying).
Also python ones would also allow self modifying. I'm always puzzled (and worried) when JS is used outside of browsers.
I'm biased as I find JS/TS rather ugly language compared to anything other basically (PHP is close second). Python is clean, C has performance, Rust is clean and has performance, Java has the biggest library and can run anywhere.
The simplicity of extending pi is in itself addictive, but even in its raw form it does the job well.
Before finding pi I had written a lot of custom stuff on top of all the provider specific CLI tools (codex, Claude, cursor-agent, Gemini) - but now I don’t have to anymore (except if I want to use my anthropic sub, which I will now cancel for that exact reason)
I just found out about pi yesterday. It's the only agent that I was able to run on RISC-V. It's quite scary that it runs commands without asking though.
Pi is good stuff and refreshingly simple and malleable.
I used it recently inside a CI workflow in GitLab to automatically create ChangeLog.md entries for commits. That + Qwen 3.5 has been pretty successful. The job starts up Pi programatically, points it at the commits in question, and tells it to explore and get all the context it needs within 600 seconds... and it works. I love that this is possible.
I’ve been extraordinarily productive with this, their $10 Go plan, and a rigorous spec-driven workflow. Haven’t touched Claude in 2 months.
I sprinkle in some billed API usage to power my task-planner and reviewer subagents (both use GPT 5.4 now).
The ability to switch models is very useful and a great learning experience. GLM, Kimi and their free models surprised me. Not the best, not perfect, but still very productive. I would be a wary shareholder if I owned a stake in the frontier labs… that moat seems to be shrinking fast.
It's been a moving target for years at this point.
Both open and closed source models have been getting better, but not sure if the open source models have really been closing the gap since DeepSeek R1.
But yes: If the top closed source models were to stop getting better today, it wouldn't take long for open source to catch up.
Can you talk more about how you leverage higher quality models for the stuff that counts? Anywhere I can read more on the philosophy of when to use each?
Sure happy to share. It’s been trial and error, but I’ve learned that for agents to reliably ship a large feature or refactor, I need a good spec (functional acceptance criteria) and I need a good plan for sequencing the work.
The big expensive models are great at planning tasks and reviewing the implementation of a task. They can better spot potential gotchas, performance or security gaps, subtle logic and nuance that cheaper models fail to notice.
The small cheap models are actually great (and fast) at generating decent code if they have the right direction up front.
So I do all the spec writing myself (with some LLM assistance), and I hand it to a Supervisor agent who coordinates between subagents. Plan -> implement -> review -> repeat until the planner says “all done”.
I switch up my models all the time (actively experimenting) but today I was using GPT 5.4 for review and planning, costing me about $0.4-$1 for a good sized task, and Kimi for implementation. Sometimes my spec takes 4-5 review loops and the cost can add up over an 8 hour day. Still cheaper than Claude Max (for now, barely).
Each agent retains a fairly small context window which seems to keep costs down and improves output. Full context can be catastrophic for some models.
As for the spec writing, this is the fun part for me, and I’ve been obsessing over this process, and the process of tracking acceptance criteria and keeping my agents aligned to it. I have a toolkit cooking, you can find in my comment history (aiming to open source it this week).
I'm building a full stack web app, simple but with real API integrations with CC.
Moving so fast that I can barely keep a hold on what I'm testing and building at the same time, just using Sonnet. It's not bad at all. A lot of the specs develop as I'm testing the features, either as an immediate or a todo / gh issue.
The moat is having researchers that can produce frontier models. When OpenCode starts building frontier models, then I'd be worried; otherwise they're just another wrapper
"OpenCode Go" (a subscription) lets you use lots of hosted open-weights frontier AI models, such as GLM-5 (currently right up there in the frontier model leaderboards) for $10 per month.
OpenCode works awesome for me. The BigPickle model is all I want. I do not throw some large work at the agent that requires lot of reasoning, thinking or decision making. It's my role to chop the work down to bite-size and ask the fantastic BigPickle to just do the damn coding or bit of explaining. It works very well with interactive sessions with small tasks. Not giving something to work over night.
I used Claude with paid subscription and codex as well and settled to OpenCode with free models.
The security concerns here are real but not unique to OpenCode. Most AI coding agents have the same fundamental problem: they need broad file system access to be useful, but that access surface is also the attack surface. The config-from-web issue is particularly bad because it's essentially remote code execution through prompt injection.
What I'd want to see from any of these tools is a clear permissions model — which files the agent can read vs write, whether it can execute commands, and an audit log of what it actually did. Claude Code's hooks system at least gives you deterministic guardrails before/after agent actions, but it's still early days for this whole category.
Granted, I just started playing around with OpenCode (but been using Codex and Claude Code since they were initially available, so not first time with agents), but anyways:
> they need broad file system access to be useful, but that access surface is also the attack surface
Do they? You give them access to one directory typically (my way is to create a temporary docker container that literally only has that directory available, copied into the container on boot, copied back to the host once the agent completed), and I don't think I've needed them to have "broad file system access" at any point, to be useful or otherwise.
So that leads me to think I'm misunderstanding either what you're saying, or what you're doing?
This is the way. If you’re not running your agent harness/framework in a container with explicit bind mounts or copy-on-build then you’re doing it wrong. Whenever I see someone complain about filesystem access and sequirity risk it’s a clear signal of incompetence imo.
Someone correct me if I'm wrong, but if you're doing bind-mounts, ensure you do read-only, if you're doing bi-directional bind mounts with docker, the agent could (and most likely know how to) create a symlink that allows them to browse outside the bind mount.
That's why I explicitly made my tooling do "Create container, copy over $PWD, once agent completes, copy back to $PWD" rather than the bind-mount stuff.
Since this is blowing up, gonna plug my opencode/claude-code plugin that allows you to annotate LLMs plans like a Google doc with strikethroughs, comments, etc. and loop with your agent until you're happy with the plan.
i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great. i also built a plugin to enable a very minimal OpenClaw alternative as a self modifying hook system over IPC as a plugin for OpenCode: https://github.com/khimaros/opencode-evolve -- and here's a deployment ready example making use of it which runs in an Incus container/VM: https://github.com/khimaros/persona
Very cool! I have been using opencode, as almost everybody else in the lab is using codex. I found the tools thing inside your own repo amazing but somehow I could not get it to reliably get opencode to write its own tools. Seems also a bit scary as there is pretty much not much security by default. I am using it in a NixOS WSL2 VM
I'm actually moving to containerised isolation. I realised the agents waste too much time trying to correctly install dependencies, not unlike a normal nixos user.
I don't use it for coding but as an agent backend. Maybe opencode was thought for coding mainly, but for me, it's incredibly good as an agent, especially when paired with skills, a fastapi server, and opencode go(minimax) is just so much intelligence at an incredibly cheap price. Plus, you can talk to it via channels if you use a claw.
The only thing I'm wondering is if they have eval frameworks (for lack of a better word). Their prompts don't seem to have changed for a while and I find greater success after testing and writing my own system prompts + modification to the harness to have the smallest most concise system prompt + dynamic prompt snippets per project.
I feel that if you want to build a coding agent / harness the first thing you should do is to build an evaluation framework to track performance for coding by having your internal metrics and task performance, instead I see most coding agents just fiddle with adding features that don't improve the core ability of a coding agent.
Now I just started looking into OpenCode yesterday, but seems you can override the system prompts by basically overloading the templates used in for example `~/.opencode/agents/build.md`, then that'd be used instead of the default "Build" system prompt.
At least from what I gathered skimming the docs earlier, might not actually work in practice, or not override all of it, but seems to be the way it works.
I've forked it locally, to be honest I haven't merged upstream in a while as I haven't seen any commits that I found relevant and would improve my usage, they seem to work on the web and desktop version which I don't use.
The changes I've made locally are:
- Added a discuss mode with almost on tools except read file, ask tool, web search only based no heuristics + being able to switch from discuss to plan mode.
Experiments:
- hashline: it doesn't bring that much benefit over the default with gpt-5.4.
- tried scribe [0]: It seems worth it as it saves context space but in worst case scenarios it fails by reading the whole file, probably worth it but I would need to experiment more with it and probably rewrite some parts.
The nice thing about opencode is that it uses sqlite and you can do experiments and then go through past conversation through code, replay and compare.
I've used it but recently moved back to plain claude code. We use claude at the company and weirdly the experience has become less and less productive using opencode. I'm a bit sad about it as it was the first experience that really clicked and got great results out of. I'm actually curious if Anthropic knows which client is used and if they negatively influence the experience on purpose. It's very difficult to prove because nothing about this is exact science.
Stupid question, but are there models worth using that specialize in a particular programming language? For instance, I'd love to be able to run a local model on my GPU that is specific to C/C++ or Python. If such a thing exists, is it worth it vs one of the cloud-based frontier models?
I'm guessing that a model which only covers a single language might be more compact and efficient vs a model trained across many languages and non-programming data.
I'm currently experimenting with (trying to) fine tune Qwen3.5 to make it better at a given language (Nim in this case); but I am quite bad at this, and honestly am unsure if it's even really fully feasible at the scale I have access to. Certainly been fun so far though, and I have a little Asus GX10 box on the way to experiment some more!
Been playing around with fine-tuning models for specific languages as well (Clojure and Rust mostly), but the persistent problem is high quality data sets, mostly I've been generating my own based on my own repositories and chat sessions, what approach are you taking for gathering the data?
My own experience trying many different models is that general intelligence of the model is more important.
If you want it to stick to better practices you have to write skills, provide references (example code it can read), and provide it with harnessing tools (linters, debuggers, etc) so the agent can iterate on its own output.
I'd really like to get more clarification on offline mode and privacy. The github issues related to privacy did not leave a good feeling, despite being initially excited. Is offline mode a thing yet? I want to use this, but I don't want my code to leave my device.
Can someone explain how Claude Code can instantly determine what file I have open and what lines I have selected in VS Code even if it's just running in a VS Code terminal instance, yet I cannot for the life of me get OpenCode to come anywhere close to that same experience?
The OpenCode docs suggest its possible, but it only works with their extension (not in an already open VS Code terminal) with a very specific keyboard shortcut and only barely at that.
I've been using opencode for a few months and really like it, both from a UX and a results perspective.
It started getting increasingly flaky with Anthropic's API recently, so I switched back to Claude Code for a couple of days. Oh my, what a night and day difference. Tokens, MCP use, everything.
For anyone reading at OpenAI, your support for OpenCode is the reason I now pay you 200 bucks a month instead.
I've been paying OpenAI 200 bucks a month for what feels like forever by now, but used OpenCode for the first time yesterday, been using Codex (and Claude Code from time to time, to see if they've caught up with Codex) since then.
But I don't use MCP, don't need anything complicated, and not sure what OpenCode actually offers on top. The UI is slightly nicer (but oh so much heavier resource usage), both projects source code seems vibecoded and the architecture is held together with hopes and dreams, but in reality, minor difference really.
Also, didn't find a way in OpenCode to do the "Fast Mode" that Codex has available, is that just not possible or am I missing some setting? Not Codex-Spark but the mode that toggles faster inference.
What would be the advantage using this over say VSCode with Copilot or Roo Code? I need to make some time to compare, but just curious if others have a good insight on things.
I started out using VSCode with their Claude plugin; it seemed like a totally unnecessary integration. A better workflow seems to just run Claude Code directly on my machine where there are fewer restrictions - it just opens a lot more possibilities on what it can do
Ok I get it now, same with the vim comment above, it seems VSCode has the more IDE setup while OpenCode is giving the vim nerdtree vibe? I'll have to take a look, it makes sense to possibly have both for different use cases I guess.
I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptions.
The harness is great. Local models are just slow enough that the subscription models are easier to use. For most of my tasks these days, the model's capability is sufficient; it is just not as snappy.
One thing I like with Aider is the fact that I can control the context by using /add explicitly on a subset of files. Can you achieve the same wit OpenCode ?
I'm curious: I'venever touched cloud models beyond a few seconds. I run a AMD395+ with the new qwen coder. Is there any intelligence difference, or is it just speed and context? At 128GB, it takes quite awhile before getting context wall.
There's a difference in intelligence. However for 90% of what I'm doing I don't really need it. The online models are just faster.
I just did a one hour vibe session today, ripping out a library dependency and replacing it with another and pushing the library to pypi. I should take my task list and let the local model replicate the work and see how it works out.
Question: How do we use Agents to Schedule and Orchestrate Farming and Agricultural production, or Manufacturing assembly machines, or Train rail transportation, or mineral and energy deposit discovery and extraction or interplanetary terraforming and mining, or nuclear reactor modulation, or water desalination automation, or plutonium electric fuel cell production with a 24,000 year half-life radiation decay, or interplanetary colonization, or physics equation creation and solving for faster-than-light travel?
If it was a somewhat unique name, then yeah maybe. But "opencode" is probably as generic as you could make it, hard to claim to be "squatting" something so well used already... Earliest project on GitHub named "opencode" seems to date back to 2010, but I'm sure there are even earlier projects too: https://github.com/search?q=opencode&type=repositories&s=upd...
you'll be surprised the name was actually a controversy on x/twitter since opencode was originally another dev's idea who joined the charmcli team. they wanted to keep that name but dax somehow (?) ended up squatting it. the charmcli team has renamed their tool to "crush" which matches their other tools a lot better than "opencode"
What caused the switch was that we're building AI solutions for sometimes price-conscious customers, so I was already familiar with the pattern of "Use a superior model for setting a standard, then fine-tuning a cheaper one to do that same work".
So I brought that into my own workflows (kind of) by using Opus 4.6 to do detailed planning and one 'exemplar' execution (with 'over documentation' of the choices), then after that, use Opus 4.6 only for planning, then "throw a load of MiniMax M2.5s at the problem".
They tend to do 90% of the job well, then I sometimes do a final pass with Opus 4.6 again to mop up any issues, this saves me a lot of tokens/money.
This pattern wasn't possible with Claude Code, thus my move to Open Code.
Interesting timing — I've been building on Cloudflare Workers
with edge-first constraints, and the resource footprint of most
AI coding tools is striking by comparison. A TypeScript agent
that uses 1GB+ RAM for a TUI feels like the wrong abstraction.
The edge computing model forces you to think differently about
state, memory, and execution — maybe that's where lighter
agentic tools will emerge.
I tried to use it but OpenCode won't even open for me on Wayland (Ubuntu 24.04), whichever terminal emulator I use. I wasn't even aware TUI could have compatibility issues with Wayland
Definitely not Wayland related, or so I doubt. I'm on wayland and never had any issues, and it's a TUI, where the terminal emulator does or does not do GPU work. What led you to that conclusion?
> On Linux, some Wayland setups can cause blank windows or compositor errors.
> If you’re on Wayland and the app is blank/crashing, try launching with OC_ALLOW_WAYLAND=1.
> If that makes things worse, remove it and try launching under an X11 session instead.
OC_ALLOW_WAYLAND=1 didn't work for me (Ubuntu 24.04)
Suggesting to use a different display server to use a TUI (!!) seems a bit wild to me. I didn't put a lot of time into investigating this so maybe there is another reason than Wayland. Anyway I'm using Pi now
That issue points out that it is probably a dependency problem.
The other problem is that they let a package manager block the UI and either swallow hard errors or unable to progress on soft errors. The errors are probably (hopefully) in some logs.
A dev oriented TUI should report unrecoverable errors on screen or at least direct you to the logs. It's not easy to get right, but if you dare to do it isn't rocket science either. They didn't dare.
I had to abandon it because of the memory leak, it would fill up all my memory in a matter of minutes. The devs don't seem to pay it much attention: https://github.com/anomalyco/opencode/issues/5363
I wish they would add back support for anthropic max/pro plans via calling the claude cli in -p mode. As I understand thats still very much allowed usage of claude code cli (as you are still using claude cli as it was intended anyway and fixes the issue of cache hits which I believe were the primary reason anthropic sent them the c&d). I love the UX from OpenCode (I loved setting it up in web mode on my home server and code from the web browser vs doing claude code over ssh) but until I can use my pro/max subscription I can't go back, the API pricing is way too much for my third world country wallet.
They had that?! I saw that some people wrote skills and plugins to call claude cli and gemini cli to still be able to use the subscription.
I would also wish that this was supported out of the box, something similar to goose cli providers or acp providers (https://block.github.io/goose/docs/guides/acp-providers).
But I don't want to spend testing yet another agent harness or change the workflow when I somewhat got used to one way of working on things (the churn is real).
Yeah, support the company that promised to help your government illegally mass surveil and mass kill people, because they support a use case slightly better than the non-mass-murdering option.
You are absolutely correct that both are evil ... as are most corporations.
Still, I feel like "will commit illegal mass murder against their own citizens" is a significant enough degree more evil. I think lots of corporations will help their government murder citizens of other countries, but very few would go so far as to agree to murder their own (fellow) citizens ... just to get a juicy contract.
I see your viewpoint but, to me, "both will happily murder you but one is better because they won't murder ME!" isn't very compelling. Like, I get it, but also it changes nothing for me. They're both bad.
It's not about "won't murder me" it's about "won't murder their own tribe". Humans are very tribal creatures, and we have all sorts of built-in societal taboos about betraying our tribe.
We also have taboos against betraying/murdering/whatever people of other tribes, but those taboos are much weaker and get relaxed sometimes (eg. in war). My point is, it takes significantly more anti-social (ie. evil) behavior to betray your own tribe, in the deepest way possible, than it does to do horrible things to other tribes.
This is just as much true for Russians murdering Ukranians as Ukranians murdering Russians, or any other conflict group: almost all Russians would consider a Russian who helps kill Russians to be more evil than a Russian who kills Ukranians (and vice versa).
Right, but I consider someone who'll murder exclusively other tribes to be infinitely closer to someone who'll murder their own tribe than to someone who won't murder anyone.
You're right, Anthropic shouldn't have even taken a moral stance here at all. They should have just gone full send and allowed everything, because there will never be satisfying some people. Why even try?
Many folks from other tools are only getting exposed to the same functionality they got used to, but it offers much more than other harnesses, especially for remote coding.
You can start a service via `opencode serve`, it can be accessed from anywhere and has great experience on mobile except a few bugs. It's a really good way to work with your agents remotely, goes really well with TailScale.
The WebUI that they have can connect to multiple OpenCode backends at once, so you may use multiple VPS-es for various projects you have and control all of them from a single place.
Lastly, there's a desktop app, but TBH I find it redundant when WebUI has everything needed.
Make no mistakes though, it's not a perfect tool, my gripes with it:
- There are random bugs with loading/restoring state of the session
- Model/Provider selection switch across sessions/projects is often annoying
- I had a bug making Sonnet/Opus unusable from mobile phone because phone's clock was 150ms ahead of laptop's (ID generation)
- Sometimes agent get randomly stuck. It especially sucks for long/nested sessions
- WebUI on laptop just completely forgot all the projects at
one day
- `opencode serve` doesn't pick up new skills automatically, it needs to be restarted
Being able to assign different models to subagents is the feature I've been wanting. I use Claude Code daily and burning the same expensive model on simple file lookups hurts. Any way to set default model routing rules, or is it manual per task?
With OpenCode, I've found that I can do this by defining agents, assigning each agent a specifically model to use. Then K manually flip to that agent when I want it or define some might rules in my global AGENTS.nd file to gives some direction and OpenCode will automatically subtask out to the agent, which then forces the use of the defined model.
- GH copilot API is a first class citizen with access to multiple providers’ models at a very good price with a pro plan
- no terminal flicker
- it seems really good with subagents
- I can’t see any terminal history inside my emacs vterm :(
The maintaining team is incredibly petty though. Tantrums when they weren't allowed to abuse Claude subscriptions and had to use the API instead. They just removed API support entirely.
‘abuse’. The same rate limits apply, the requests still go to the same endpoints.
Even as a CC user I’m glad someone is forcing the discussion.
My prediction: within two years ‘model neutrality’ will be a topic of debate. Creating lock-in through discount pricing is anti-competitive. The model provider is the ISP; the tool, the website.
> The same rate limits apply, the requests still go to the same endpoints.
That is not the point. That is a mere technicality.
You signed a contract. If you don't ignore the terms of the contract to use the product in a way that is explicitly prohibited, you're abusing the product. It is as simple as that.
They offer a separate product (API) if you don't like the terms of the contract.
Also, if you really want to get technical: the limits are under the assumption that caching works as intended, which requires control of the client. 3P clients suck at caching and increase costs. But that is not the overarching point.
> Creating lock-in through discount pricing is anti-competitive.
Literally everyone does this. OpenAI is doing this with Codex, far more than Anthropic is. It's not great but players much bigger than Anthropic are using discount pricing to create an anti-competitive advantage.
> Literally everyone does this. OpenAI is doing this with Codex, far more than Anthropic is.
And yet, OpenAI have publicly said they welcome OpenCode users to use their subscription package. So how are they being anti-competitive "far more" than Anthropic?
Anthropic has zero problems with API billing, there's no chance they told him to rip that out.
Reading through his X comments and GitHub comments he is behaving immaturely. I don't trust what he's saying here. Ripping out Claude API support was just throwing a tantrum. Weird given his age - he's old enough to be more mature.
The MCP (Model Context Protocol) support is what makes this interesting to me. Most coding agents treat the file system and shell as the only surfaces — MCP opens up the possibility of connecting to any structured data source or API as a first-class tool without custom integration work each time.
Curious how the context window management works in practice. With large repos, the "what files to include" problem tends to dominate — does it have a strategy beyond embedding-based retrieval, or is that the main approach here?
I had been using open code and admire they effort to create something huge and help a lot of developers around the world, connecting LLM our daily work without use a browser!
Things that make an an OpenCode fanboy
1. OpenCode source code is even more awesome. I have learned so much from the way they have organized tools, agents, settings and prompts.
2. models.dev is an amazing free resource of LLM endpoints these guys have put together
3. OpenCode Zen almost always has a FREE coding model that you can use for all kinds of work. I recently used the free tier to organize and rename all my documents.
I use bubblewrap. This ensures it only has access to the current working directory and its own configuration. No ability to commit or push (since it doesn't have access to ssh keys) or try to run aws commands (no access to awscli configuration) and so on. It can read anything from my .envrc, since it doesn't have access to direnv or the parent directory. You could lock down the network even further if you wanted to limit web searches.
I use this. I run it in a sandbox[0]. I run it inside Emacs vterm so it's really quick for me to jump back and forth between this and magit, which I use to review what it's done.
I really should look into more "native" Emacs options as I find using vterm a bit of a clunky hack. But I'm just not that excited about this stuff right now. I use it because I'm lazy, that's all. Right now I'm actually getting into woodwork.
Honestly I was a Claude code only guy for a while. I switched to opencode and I’m not going back.
IMO, the web UI is a killer feature - it’s got just enough to be an agent manager - without any fluff. I run it on my remote VMs and connect over HTTP.
You do not "write" code. Stop these euphemisms. It is an intellectual prosthetic for feeble minded people that plagiarizes code by written by others. And it connects to the currently "free" providers who own the means of plagiarizing.
There is nothing open about it. Please do not abuse the term "open" like in OpenBSD.
This is very interesting. This could allow custom harnesses to be used economically with Opus. Depending on the usage limits, this may be cheaper than their API.
You can scroll down literally two messages in the Github issue you linked:
> there isnt any telemetry, the open telemetry thing is if you want to get spans like the ai sdk has spans to track tokens and stuff but we dont send them anywhere and they arent enabled either
> most likely these requests are for models.dev (our models api which allows us to update the models list without needing new releases)
> There is currently no option to change this behavior, no startup flag, nothing. You do not have the option to serve the web app locally, using `opencode web` just automatically opens the browser with the proxied web app, not a true locally served UI.
That is the address of their hosted WebUI which connects to an OpenCode server on your localhost. Would be nice if there was an option to selfhost it, but it is nowhere near as bad as "proxying all requests".
I used Codex for a long time. It's definitely better than Claude Code due to being open source, but opencode is nicer to use. Good hotkeys, plan/build modes, fast and easy model switching, good mcp support. Supports skills, is not the fastest but good enough.
Just a data point, I would need to use it for my workflows. I do have a monorepo with a root level claude.md, and project level claude.md files for backend/frontend.
I started with Codex, then switched to OpenCode, then switched to Codex.
OpenCode just has more bugs, it's incredibly derivative so it doesn't really do anything else than Codex.
The advantage of OpenCode is that it can use any underlying model, but that's a disadvantage because it breaks the native integration. If you use Opus + Claude Code, or Gpt-Codex + Codex App, you are using it the way it was designed to be used.
If you don't actually use different models, or plan to switch, or somehow value vendor neutrality strategically, you are paying a large cost without much reward.
This is in general a rule, vendor neutrality is often seen as a generic positive, but it is actually a tradeoff. If you just build on top of AWS for example, you make use of it's features and build much faster and simpler than if you use Terraform.
What I don't understand is that, if coding agents are making coding obsolete, why do these vibe coders not choose a language that doesn't set their users' compute resources on fire? Just vibe rust or golang for their cli tools, no one reviews code slop nowadays anyway /s.
I do not understand the insistence on using JavaScript for command line tools. I don't use rust at all, but if I'm making a vibe coded cli I'm picking rust or golang. Not zig because coding agents can't handle the breaking changes. What better test of agentic coders' conviction in their belief in AI than to vibe a language they can't read.
The topic at hand seems to shift the quality of the discussion greatly these days. Many people have thoughts on coding agents because they are aimed at the lower quartiles of coders. Far less have detailed opinions on other ways they could wield a Markov model.
Just remember, OpenCode is sending telemetry to their own servers, even when you're using your own locally hosted models. There are no environment variables, flags, or other configuration options to disable this behavior.¹
At least you can easily turn off telemetry in Claude Code - just set CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC to 1.
You can use Claude Code with llama.cpp and vLLM, too right out of the box with no additional software necessary, just point ANTHROPIC_BASE_URL at your inference server of choice, with any value in ANTHROPIC_API_KEY.
Some people think that Anthropic could disable this at any time, but that's not really true - you can disable automatic updates and back up and reuse native Claude Code binaries, ensuring Anthropic cannot change your existing local Claude Code binary's behavior.
With that said, I like the idea of an open source TUI agent that won't spy on me without my consent and no way to disable it much better than a closed source TUI agent that I can effectively neuter telemetry on, but sadly, OpenCode is not the former. It's just another piece of VC-funded spyware that's destined for enshittification.
Are you sure that endpoint is sending all traffic to opencode? I'm not familiar with Hono but it looks like a catch all route if none of the above match and is used to serve the front-end web interface?
More than that, it's an extremely large and complex TypeScript code base — probably larger and more complex than it needs to be — and (partly as a result) it's fairly resource inefficient (often uses 1GB of RAM or more. For a TUI).
On top of that, at least I personally find the TUI to be overbearing and a little bit buggy, and the agent to be so full of features that I don't really need — also mildly buggy — that it sort of becomes hard to use and remember how everything is supposed to work and interact.
That's (one of the reasons) why I'm favoring Codex over Claude Code.
Claude Code is an... Electron app (for a TUI? WTH?) and Codex is Rust. The difference is tangible: the former feels sluggish and does some odd redrawing when the terminal size changes, while the latter definitely feels more snappy to me (leaving aside that GPT's responses also seem more concise). At some point, I had both chewing concurrently on the same machine and same project, and Claude Code was using multiple GBs of RAM and 100% CPU whereas Codex was happy with 80 MB and 6%.
Performance _is_ a feature and I'm afraid the amounts of code AI produces without supervision lead to an amount of bloat we haven't seen before...
The redraw glitches you’re referring to are actually signs of what I consider to be a pretty major feature, a reason to use `claude` instead of `codex` or `opencode`: `claude` doesn’t use the alternate screen, whereas the other two do. Meaning that it uses the standard screen buffer, meaning that your chat history is in the terminal (or multiplexer) scrollback. I much prefer that, and I totally get why they’ve put so much effort into getting it to work well.
In that context handling SIGWINCH has some issues and trickiness. Well worth the tradeoff, imo.
on my m1, claude is noticeably slower when starting, but it feels ok after that.
The difference in feel between Codex and Claude Code is obvious.
The whole thing is vibed anyway, I'm sure they could get it done in a week or two for their quality standards.
What would make go more "accessible to contributors" than Rust?
CC isn't foss in the first place, so the previous comment falls short.
[1] https://opencode.ai/docs/config/#precedence-order
[2] https://github.com/anomalyco/opencode/issues/10939
You need to set an explicit "small model" in OpenCode to disable that.
The small_model option configures a separate model for lightweight tasks like title generation. By default, OpenCode tries to use a cheaper model if one is available from your provider, otherwise it falls back to your main model.
I would expect that if you set a local model it would just use the same model. Or if for example you set GPT as main model, it would use something else from OpenAI. I see no mentions of Grok as default
[1] https://opencode.ai/docs/config/
Have fun on windows - automatic no from me. https://github.com/anomalyco/opencode/issues?q=is%3Aissue%20...
this is what i notice with openclaw as well. there have been releases where they break production features. unfortunately this is what happens when code becomes a commidity, everyone thinks that shipping fast is the moat but at the expense of suboptimality since they know a fix can be implemented quickly on the next release.
I’m sure we’ll all learn a lot from these early days of agentic coding.
So far what I am learning (from watching all of this) is that our constant claims that quality and security matter seem to not be true on average. Depressingly.
But as agents move from prototypes to production, the calculus changes. Production systems need: - Memory continuity across sessions - Predictable behavior across updates - Security boundaries that don't leak
The tools that prioritize these will win the enterprise market. The ones that don't will stay in the prototype/hobbyist space.
We're still in the "move fast" phase, but the "break things" part is starting to hurt real users. The pendulum will swing back.
The reason for this is that product development involves making decisions which can later be classified as good or bad decisions.
The good decisions must remain stable, while the bad decisions must remain open to change and therefore remain unstable.
The AI doesn't know anything about the user experience, which means it will inevitably change the good decisions as well.
Only for the non-pro users. After all, those users were happy to use excel to write the programs.
What we're seeing now is that more and more developers find they are happy with even less determinism than the Excel process.
Maybe they're right; maybe software doesn't need any coherence, stability, security or even correctness. Maybe the class of software they produce doesn't need those things.
I, unfortunately, am unable to adopt this view.
I'm 13 years into this industry, this is the first I'm hearing of this.
Also most of the long running enterprise projects I’ve seen - there was one that had been around for like 10 years and like about 75% of the devs I hadn’t even heard of and none of the original ones were in the project at all.
The thing had no less than three auditing mechanisms, three ways of interacting with the database, mixed naming conventions, like two validation mechanisms none of which were what Spring recommended and also configurations versioned for app servers that weren’t even in use.
This was all before AI, it’s not like you need it for projects to turn into slop and AI slop isn’t that much different from human slop (none of them gave a shit about ADRs or proper docs on why things are done a certain way, though Wiki had some fossilized meeting notes with nothing actually useful) except that AI can produce this stuff more quickly.
When encountered, I just relied on writing tests and reworking the older slop with something newer (with better AI models and tooling) and the overall quality improved.
All code is not fungible, "irreverent code that kinda looks okay at first glance" might be a commodity, but well-tested, well-designed and well-understood code is what's valuable.
Code today can be as verbose and ugly as ever, because from here on out, fewer people are going to read it, understand and care about it.
What's valuable, and you know this I think, is how much money your software will sell for, not how fine and polished your code is.
Code was a liability. Today it's a liability that cost much much less.
How much value are you going to be able to extract over its lifetime once your customers want to see some additional features or improvements?
How much expensive maintenance burden are you incurring once any change (human or LLM generated) is likely to introduce bugs you have no better way of identifying than shipping to your paying customers?
Maybe LLM+tooling is going to get there with producing a comprehensible and well tested system but my anectodal experience is not promising. I find that AI is great until you hit its limit on a topic and then it will merrily generate tokens in a loop suggesting the same won't-work-fix forever.
The whole thing reminds me a bit of the many RAD tools that were supposed to 'solve' programming. While it was easy to start and produce something with those tools, at some point you started spending way too much time working around the limitations and wished you started from scratch without it.
There are limits to what even AI can do to code, within practical time-limits. Using AI also costs money. So, easier it is to maintain and evolve a piece of software, the cheaper it will be to the owners of that application.
[1] https://museumoffailure.com/exhibition/wonka-chocolate-exper...
Code that has not been thoroughly tested is a greater liability, not a lesser one.l, the faster you can write it.
I expect that from something guiding the market, but there have been times where stuff changes, and it isn't even clear if it is a bug or a permanent decision. I suspect they don't even know.
I wonder how much of this is because the maintainers are using OpenCode to vibe the code for OpenCode.
I would (incorrectly) assume that a product like this would be heavily tested via AI - why not? AI should be writing all the code, so why would the humans not invest in and require extreme levels of testing since AI is really good at that?
Like Rails/DHH was one phase, Git/GitHub another.
And right now it's kinda Claude Code. But they're so obviously really bad at development that it feels like a MLM scam.
I'm just describing the feeling I'm getting, perhaps badly. I use Claude, I recommended Claude for the company I worked at. But by god they're bloody awful at development.
It feels like the point where someone else steps in with a rock solid, dependable, competitor and then everyone forgets Claude Code ever existed.
https://x.com/thdxr/status/2031377117007454421
[0] https://www.reddit.com/r/LocalLLaMA/comments/1rv690j/opencod...
[1] https://github.com/standardnguyen/rolandcode
that #12446 PR hasn't even been resolved to won't merge and last change was a week ago (in a repo with 1.8k+ open PRs)
Must be a karmic response from “Free” /s
The choice isn't "telemetry or you're blindfolded", the other options include actually interacting with your userbase. Surveys exist, interviews exist, focus groups exist, fostering communities that you can engage is a thing, etc.
For example, I was recruited and paid $500 to spend an hour on a panel discussing what developers want out of platforms like DigitalOcean, what we don't like, where our pain points are. I put the dollar amount there only to emphasize how valuable such information is from one user. You don't get that kind of information from telemetry.
We all know it’s extremely, extremely hard to interact with your userbase.
> For example I was paid $500 an hour
+the time to find volunteers doubled that, so for $1000 an hour x 10 user interviews, a free software can have feedback from 0.001% of their users. I dislike telemetry, but it’s a lie to say it’s optional.
—a company with no telemetry on neither of our downloadable or cloud product.
On the contrary, your users will tell you what you need to know, you just have to pay attention.
> I dislike telemetry, but it’s a lie to say it’s optional.
The lie is believing it’s necessary. Software was successful before telemetry was a thing, and tools without telemetry continue to be successful. Plenty of independent developers ship zero telemetry in their products and continue to be successful.
Interesting you say this because I'd say the opposite is true historically, especially in the systems software community and among older folks. "Do one thing and do it well" seems to be the prevailing mindset behind many foundational tools. I think this why so many are/were irked by systemd. On the other hand newer tools that are more heavily marketed and often have some commercial angle seem to be in a perpetual state of tacking on new features in lieu of refining their raison d'etre.
OpenCode has been much more stable for me in the 6 months or so that I’ve been comparing the two in earnest.
Is Claude Code like this too? I wonder if Pi is any better.
A big downside would be paying actual cost price for tokens but on the other hand, I wouldn't be tied to Google's model backend which is also extremely flaky and unable to meet demand a lot of the time. If I could get real work done with open models (no idea if that's the case yet) and switch providers when a given provider falls over, that would be great.
I'm very happy with Pi myself (running it on a small VPS so that I don't need to do sandboxing shenanigans).
On top of that. Open code go was a complete scam. It was not advertised as having lower quality models when I paid and glm5 was broken vs another provider, returning gibberish and very dumb on the same prompt
That being said, I do prefer OpenCode to Codex and Claude Code.
(I'm also hating on TS/JS: but some day some AI will port it to Rust, right?)
CC I have the least experience with. It just seemed buggy and unpolished to me. Codex was fine, but there was something about it that just didn't feel right. It seemed fined for code tasks but just as often I want to do research or discuss the code base, and for whatever reason I seemed to get terse less useful answers using Codex even when it's backed by the same model.
OpenCode works well, I haven't had any issues with bugs or things breaking, and it just felt comfortable to use right from the jump.
Tbf, this seems exactly like Claude Code, they are releasing about one new version per day, sometimes even multiple per day. It’s a bit annoying constantly getting those messages saying to upgrade cc to the latest version
It's annoying how I always get that "claude code has a native installer xyz please upgrade" message
[1] https://github.com/badlogic/pi-mono/tree/main/packages/codin...
I build VT Code with Tree-sitter for semantic understanding and OS-native sandboxing. It's still early but I confident it usable. I hope you'll give it a try.
But we did a lot of work on improving the experience, both on UX, performance, and the actual reliability of the agent itself.
I would suggest you to give it a try.
Also, non-interactive support, useful for some workflows:
https://github.com/charmbracelet/crush/releases/tag/v0.48.0
https://github.com/charmbracelet/crush/releases/tag/v0.50.0
I then tried running other options like picoclaw/picocode etc but they were all really hard to manage/create
The UI/UX I want is that I can just put my free openrouter api key in and then I am ready to go to get access to free models like Arcee AI right now
After reading your comments/I read this thread, I tried crush by charmbracelet again and it gives the UI/UX that I want.
I am definitely impressed by crush/ the charm team. They are on HN and they work great for me, highly recommended if you want something which can work on low constrained devices
I do feel like Charm's TUI's are too beautiful in the sense that running a connection over SSH can delay so when I tried to copy some things, the delay made things less copy-able but overall, I think that I am using Crush and I am happy for the most part :-)
Edit: That being said, just as I was typing this, Crush took all the Free requests from Openrouter that I get for free so it might be a bit of minor issue but overall its not much of an issue from Crush side, so still overall, my point is that Crush is worth checking out
Kudos to the CharmBracelet team for making awesome golang applications!
Using AI to generate all your code only really makes sense if you prioritize shipping features as fast as possible over the quality, stability and efficiency of the code, because that's the only case in which the actual act of writing code is the bottleneck.
Personally, I find this idea that "coding isn't the bottleneck" completely preposterous. Getting all of the API documentation, the syntax, organizing and typing out all of the text, finding the correct places in the code base and understanding the code base in general, dealing with silly compiler errors and type errors, writing a ton of error handling, dealing with the inevitable and inoraticable boilerplate of programming (unless you're one of those people that believe macros are actually a good idea and would meaningfully solve this), all are a regular and substantial occurrence, even if you aren't writing thousands of lines of code a day. And you need to write code in order to be able to get a sense for the limitations of the technology you're using and the shape of the problem you're dealing with in order to then come up with and iterate on a better architecture or approach to the problem. And you need to see your program running in order to evaluate whether it's functionality and design a satisfactory and then to iterate on that. So coding is actually the upfront costs that you need to pay in order to and even start properly thinking about a problem. So being able to get a prototype out quickly is very important. Also, I find it hard to believe that you've never been in a situation where you wanted to make a simple change or refactor that would have resulted in needing to update 15 different call sites to do properly in a way that was just slightly variable enough or complex enough that editor macros or IDE refactoring capabilities wouldn't be capable of.
That's not to mention the fact that if agentic coding can make deploying faster, then it can also make deploying the same amount at the same cadence easier and more relaxing.
Which one you think companies prefer? Or if you're a consulting business, which one do you think your clients prefer?
I have yet to actually see a single example of the latter, though. OpenCode isn't an isolated case - every project with heavy AI involvement that I've personally examined or used suffers from serious architectural issues, tons of obvious bugs and quirks, or both. And these are mostly independent open source projects, where corporate interests are (hopefully) not an influence.
I will continue to believe it's not actually possible until I am proven wrong with concrete examples. The incentives just aren't there. It's easy to say "just mindlessly follow X principle and your software will be good", where X is usually some variation of "just add more tests", "just add more agents", "just spend more time planning" etc. but I choose to believe that good software cannot be created without the involvement of someone who has a passion for writing good software - someone who wouldn't want to let an LLM do the job for them in the first place.
That's a complete strawman of what I — or others trying to learn how to use coding agents to increase quality, like Simon Willison or the Oxide team — am saying.
> but I choose to believe that good software cannot be created without the involvement of someone who has a passion for writing good software - someone who wouldn't want to let an LLM do the job for them in the first place.
This is just a no true Scotsman. I prefer to use coding agents because they don't forget details, or get exhausted, or overwhelmed, or lazy, or give up, ever — whereas I might. Therefore, they allow me to do all of the things that improve code and software quality more extensively and thoroughly, like refactors, performance improvements, and tests among other things (because yes, there is no single panacea). Furthermore, I do still care about the clarity, concision, modularity, referential transparency, separation of concerns, local reasonability, cognitive load, and other good qualities of the code, because if those aren't kept up a) I can't review the code effectively or debug things as easily when they go wrong, b) the agent itself will struggle to male changes without breaking other things, and struggle to debug, c) those things often eventually effect the quality of the end state software.
Additionally, what you say is empirically false. Many people who do deeply value quality software and code quality, such as the creators of Flask, Redis, and SerenityOS/Ladybird, all use and value agentic coding.
Just because you haven't seen good quality software with a large amount of agentic influence doesn't mean it isn't possible. That's very close minded.
I have things to criticize about it, their approach to security and pulling in code being my main one, but over all it’s the most complete solution I’ve found.
They have a server/client architecture, a client SDK, a pretty good web UI and use pretty standard technologies.
The extensibility story is good and just seems like the right paradigms mostly, with agents, skills, plugins and providers.
They also ship very fast, both for good and bad, I’ve personally enjoyed the rapid improvements (~2 days from criticizing not being able to disable the default provider in the web ui to being able to).
I think OpenCode has a pretty bright future and so far I think that my issues with it should be pretty fixable. The amount of tasteful choices they’ve made dwarfs the few untasteful ones for me so far.
To change that, you need to set a custom "small model" in the settings.
More importantly, the current dev branch source for packages/opencode/src/session/summary.ts shows summarizeMessage() now only computes diffs and updates the message summary object; it does not make an LLM call there anymore. The current code path calls summarizeSession() and summarizeMessage(), and summarizeMessage() just filters messages, computes diffs, sets userMsg.summary.diffs, and saves the message.
https://github.com/anomalyco/opencode/blob/dev/packages/open...
https://old.reddit.com/r/LocalLLaMA/comments/1rv690j/opencod...
They also don't let you run all local models, but specific whitelisted by another 3rd party: https://github.com/anomalyco/opencode/issues/4232
Everything you read on the internet seems exaggerated today. Especially true for reddit, and especially especially true for r/LocalLllama which is a former shadow of itself. Today it's mostly sockpuppets pushing various tools and models, and other sockpuppets trying to push misinformation about their competitors tools/models.
it will use whatever small model there is in your provider
we had a fallback where we provided free small models if your provider did not have one (gpt nano)
some configs fell back to this unexpectedly which upset people so we removed it
Imagine someone using it at work, where they are only allowed to use a GitHub Copilot Business subscription (which is supported in OpenCode). Now they have sent proprietary code to a third party, and don't even know they're doing it.
I really like how their subagents work, as a bonus I get to choose which model is in which agent. Sadly I have to resort to the mess that Anthropic calls Claude Code
From what I've heard, the metrics used by Anthropic to detect unauthorized clients is pretty easy to sidestep if you look at the existing solutions out there. Better than getting your account banned.
The belief is that the subscriptions are subsidized by them (or just heavily cut into profit margins) so for whatever reason they're trying to maintain control over the harness - maybe to gather more usage analytics and gain an edge over competitors and improve their models better to work with it, or perhaps to route certain requests to Haiku or Sonnet instead of using Opus for everything, to cut down on the compute.
Given the ample usage limits, I personally just use Claude Code now with their 100 USD per month subscription because it gives me the best value - kind of sucks that they won't support other harnesses though (especially custom GUIs for managing parallel tasks/projects). OpenCode never worked well for me on Windows though, also used Codex and Gemini CLI.
You can point Claude Code at a local inference server (e.g. llama.cpp, vLLM) and see which model names it sends each request to. It's not hard to do a MITM against it either. Claude Code does send some requests to Haiku, but not the ones you're making with whatever model you have it set to - these are tool result processing requests, conversation summary / title generation requests, etc - low complexity background stuff.
Now, Anthropic could simply take requests to their Opus model and internally route them to Sonnet on the server side, but then it wouldn't really matter which harness was used or what the client requests anyway, as this would be happening server-side.
Actually curious to hear what others think about why Anthropic is so set on disallowing 3rd party tools on subscriptions.
So they have to move up the stack to higher margin business solutions. Which is why they offer subsidized subscription plans in the first place. It’s a marketing cost. But they want those marketing dollars to drive up the stack not commodity inference use cases.
When setting your token limits, their economics calculations likely assume that those optimizations are going to work. If you're using a different agent, you're basically underpaying for your tokens.
Build the single pane of glass everyone uses. Offer it under cost. Salt the earth and kill everything else that moves.
Nobody can afford to run alternative interfaces, so they die. This game is as old as time. Remember Reddit apps? Alternative Twitter clients?
In a few years, CC will be the only survivor and viable option.
It also kneecaps attempts to distill Opus.
It’s not like moving from android to iOS.
API = way more expensive, allowed to use on your terms without anthropic hindering you.
One-price-per-month subscriptions (Claude Code Pro/MAX @ $20/$100/$200 a month) use a different authentication mechanism, OAUTH. The useful difference is you get a lot more inference than you can for the same cost using the API but they require you to use Claude Code as a client.
Some clients have made it simple to use your subscription key with them and they are getting cease and desist letters.
(Ok, technically o1-pro is even more expensive, but I'm assuming that's a "please move on" pricing)
I'd rather switch to OpenAI than give up my favorite harness.
For me it's $0.8/kWh during peak, $0.47 off peak, and super off peak of $0.15. I accidentally left a little mini 500W heater on all day, while I was out, costing > 5% of your whole month!
Musk was the largest individual political donor of the 2024 election [1] and Greg Brockman was the largest donor to Trump's "MAGA Inc" super PAC [2]
[1] https://www.washingtonpost.com/technology/2024/12/06/elon-mu...
[2] https://www.theverge.com/ai-artificial-intelligence/867947/o...
EDIT: The system I bought last summer for $1980 and just took delivery of in October, Beelink GTR 9 Pro, is now $2999.... wow...
https://www.youtube.com/live/z0JYVTAqeQM?si=oLvyLlZiFLTxL7p0
Long tool outputs/command outputs everything in my harness is spilled over to the filesystem. Context messages are truncated and split to filesystem with a breadcrumb for retrieving the full message.
Works really well.
Assuming you pay per token, which seems like a really strange workflow to lock yourself into at this point. Neither paid monthly plans nor local models suffer from that issue.
I tried once to use APIs for agents but seeing a counter of money go up and eventually landing at like $20 for one change, made it really hard to justify. I'd rather pay $200/month before I'd be OK with that sort of experience.
https://github.com/Vibecodelicious/opencode
Pi is refreshingly minimal in terms of system prompts, but still works really well and that makes me wonder whether other harnesses are overdoing. Look at OpenCode's prompts, for instance - long, mostly based on feels and IMO unnecessary. I would've liked to just overwrite OC's system prompts with Pi's (to get other features that Pi doesn't have) but that isn't possible today (without maintaining a custom fork)
JS is not something that was developed with CLI in mind and on top of that that language does not lend itself to be good for LLM generation as it has pretty weak validation compared to e.g. Rust, or event C, even python.
Not to mention memory usage or performance.
It’s simply one of the most productive languages. It actually has a very strong type system, while still being a dynamic language that doesn’t have to be compiled, leading to very fast iteration. It’s also THE language you use when writing UIs. Execution is actually pretty fast through the runtimes we have available nowadays.
The only other interpreted language is Python and that thoroughly feels like a toy in comparison (typing situation still very much in progress, very weak ORM situation, not even a usable package manger until recently!).
I can’t find the tweet from Mario (the author), but he prefers the Typescript/npm ecosystem for non-performance critical systems because it hits a sweet spot for him. I admire his work and he’s a real polyglot, so I tend to think he has done his homework. You’ll find pi memory usage quite low btw.
Also python ones would also allow self modifying. I'm always puzzled (and worried) when JS is used outside of browsers.
I'm biased as I find JS/TS rather ugly language compared to anything other basically (PHP is close second). Python is clean, C has performance, Rust is clean and has performance, Java has the biggest library and can run anywhere.
The simplicity of extending pi is in itself addictive, but even in its raw form it does the job well.
Before finding pi I had written a lot of custom stuff on top of all the provider specific CLI tools (codex, Claude, cursor-agent, Gemini) - but now I don’t have to anymore (except if I want to use my anthropic sub, which I will now cancel for that exact reason)
that is actually really nice
I’m sure there’s a more elegant way to say this, but OpenCode feels like an open source Claude Code, while pi feels like an open source coding agent.
I used it recently inside a CI workflow in GitLab to automatically create ChangeLog.md entries for commits. That + Qwen 3.5 has been pretty successful. The job starts up Pi programatically, points it at the commits in question, and tells it to explore and get all the context it needs within 600 seconds... and it works. I love that this is possible.
I sprinkle in some billed API usage to power my task-planner and reviewer subagents (both use GPT 5.4 now).
The ability to switch models is very useful and a great learning experience. GLM, Kimi and their free models surprised me. Not the best, not perfect, but still very productive. I would be a wary shareholder if I owned a stake in the frontier labs… that moat seems to be shrinking fast.
It's been a moving target for years at this point.
Both open and closed source models have been getting better, but not sure if the open source models have really been closing the gap since DeepSeek R1.
But yes: If the top closed source models were to stop getting better today, it wouldn't take long for open source to catch up.
The big expensive models are great at planning tasks and reviewing the implementation of a task. They can better spot potential gotchas, performance or security gaps, subtle logic and nuance that cheaper models fail to notice.
The small cheap models are actually great (and fast) at generating decent code if they have the right direction up front.
So I do all the spec writing myself (with some LLM assistance), and I hand it to a Supervisor agent who coordinates between subagents. Plan -> implement -> review -> repeat until the planner says “all done”.
I switch up my models all the time (actively experimenting) but today I was using GPT 5.4 for review and planning, costing me about $0.4-$1 for a good sized task, and Kimi for implementation. Sometimes my spec takes 4-5 review loops and the cost can add up over an 8 hour day. Still cheaper than Claude Max (for now, barely).
Each agent retains a fairly small context window which seems to keep costs down and improves output. Full context can be catastrophic for some models.
As for the spec writing, this is the fun part for me, and I’ve been obsessing over this process, and the process of tracking acceptance criteria and keeping my agents aligned to it. I have a toolkit cooking, you can find in my comment history (aiming to open source it this week).
I'm building a full stack web app, simple but with real API integrations with CC.
Moving so fast that I can barely keep a hold on what I'm testing and building at the same time, just using Sonnet. It's not bad at all. A lot of the specs develop as I'm testing the features, either as an immediate or a todo / gh issue.
How can you manage an agentic flow?
I used Claude with paid subscription and codex as well and settled to OpenCode with free models.
What I'd want to see from any of these tools is a clear permissions model — which files the agent can read vs write, whether it can execute commands, and an audit log of what it actually did. Claude Code's hooks system at least gives you deterministic guardrails before/after agent actions, but it's still early days for this whole category.
> they need broad file system access to be useful, but that access surface is also the attack surface
Do they? You give them access to one directory typically (my way is to create a temporary docker container that literally only has that directory available, copied into the container on boot, copied back to the host once the agent completed), and I don't think I've needed them to have "broad file system access" at any point, to be useful or otherwise.
So that leads me to think I'm misunderstanding either what you're saying, or what you're doing?
Someone correct me if I'm wrong, but if you're doing bind-mounts, ensure you do read-only, if you're doing bi-directional bind mounts with docker, the agent could (and most likely know how to) create a symlink that allows them to browse outside the bind mount.
That's why I explicitly made my tooling do "Create container, copy over $PWD, once agent completes, copy back to $PWD" rather than the bind-mount stuff.
OpenCode has no sandboxing, as far as I know.
That makes Codex a much better choice for security.
[1] https://developers.openai.com/codex/concepts/sandboxing
https://greywall.io/
https://github.com/ndom91/open-plan-annotator
I'm actually moving to containerised isolation. I realised the agents waste too much time trying to correctly install dependencies, not unlike a normal nixos user.
Coding is mostly "agentic" so I'm bit puzzled.
https://opencode.ai/docs/agents/
I feel that if you want to build a coding agent / harness the first thing you should do is to build an evaluation framework to track performance for coding by having your internal metrics and task performance, instead I see most coding agents just fiddle with adding features that don't improve the core ability of a coding agent.
I considered creating a PR for that, but found that creating new agents instead worked fine for me.
Now I just started looking into OpenCode yesterday, but seems you can override the system prompts by basically overloading the templates used in for example `~/.opencode/agents/build.md`, then that'd be used instead of the default "Build" system prompt.
At least from what I gathered skimming the docs earlier, might not actually work in practice, or not override all of it, but seems to be the way it works.
The changes I've made locally are:
- Added a discuss mode with almost on tools except read file, ask tool, web search only based no heuristics + being able to switch from discuss to plan mode.
Experiments:
- hashline: it doesn't bring that much benefit over the default with gpt-5.4.
- tried scribe [0]: It seems worth it as it saves context space but in worst case scenarios it fails by reading the whole file, probably worth it but I would need to experiment more with it and probably rewrite some parts.
The nice thing about opencode is that it uses sqlite and you can do experiments and then go through past conversation through code, replay and compare.
[0] https://github.com/sibyllinesoft/scribe
I'm guessing that a model which only covers a single language might be more compact and efficient vs a model trained across many languages and non-programming data.
If you want it to stick to better practices you have to write skills, provide references (example code it can read), and provide it with harnessing tools (linters, debuggers, etc) so the agent can iterate on its own output.
The OpenCode docs suggest its possible, but it only works with their extension (not in an already open VS Code terminal) with a very specific keyboard shortcut and only barely at that.
It started getting increasingly flaky with Anthropic's API recently, so I switched back to Claude Code for a couple of days. Oh my, what a night and day difference. Tokens, MCP use, everything.
For anyone reading at OpenAI, your support for OpenCode is the reason I now pay you 200 bucks a month instead.
But I don't use MCP, don't need anything complicated, and not sure what OpenCode actually offers on top. The UI is slightly nicer (but oh so much heavier resource usage), both projects source code seems vibecoded and the architecture is held together with hopes and dreams, but in reality, minor difference really.
Also, didn't find a way in OpenCode to do the "Fast Mode" that Codex has available, is that just not possible or am I missing some setting? Not Codex-Spark but the mode that toggles faster inference.
I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptions.
The harness is great. Local models are just slow enough that the subscription models are easier to use. For most of my tasks these days, the model's capability is sufficient; it is just not as snappy.
I just did a one hour vibe session today, ripping out a library dependency and replacing it with another and pushing the library to pypi. I should take my task list and let the local model replicate the work and see how it works out.
- With love The Official Pink Eye #ThereIsNoOther
https://opencode.de/
Hugely grateful for what they do.
What caused the switch was that we're building AI solutions for sometimes price-conscious customers, so I was already familiar with the pattern of "Use a superior model for setting a standard, then fine-tuning a cheaper one to do that same work".
So I brought that into my own workflows (kind of) by using Opus 4.6 to do detailed planning and one 'exemplar' execution (with 'over documentation' of the choices), then after that, use Opus 4.6 only for planning, then "throw a load of MiniMax M2.5s at the problem".
They tend to do 90% of the job well, then I sometimes do a final pass with Opus 4.6 again to mop up any issues, this saves me a lot of tokens/money.
This pattern wasn't possible with Claude Code, thus my move to Open Code.
Edit: it's not. https://github.blog/changelog/2026-01-16-github-copilot-now-...
They must be eating insane amounts of $$$ for this. I wouldn't expect it to last
See https://models.dev for a comparison against the normal "vanilla" API.
They shouldn't, as long as your terminal emulator doesn't. Why do you think it's Wayland related?
It works perfectly fine on Niri, Hyprland and other Wayland WMs.
What problem do you have?
I didn't dig further
Seems like there's many github issues about this actually
https://github.com/anomalyco/opencode/issues/14336
https://github.com/anomalyco/opencode/issues/14636
https://github.com/anomalyco/opencode/issues/14335
If you respond twice to their theme query probes, the whole thing bricks. Or if you're slightly out of order. It's very delicate.
And then the official docs: https://opencode.ai/docs/troubleshooting/#linux-wayland--x11...
> Linux: Wayland / X11 issues
> On Linux, some Wayland setups can cause blank windows or compositor errors.
> If you’re on Wayland and the app is blank/crashing, try launching with OC_ALLOW_WAYLAND=1.
> If that makes things worse, remove it and try launching under an X11 session instead.
OC_ALLOW_WAYLAND=1 didn't work for me (Ubuntu 24.04)
Suggesting to use a different display server to use a TUI (!!) seems a bit wild to me. I didn't put a lot of time into investigating this so maybe there is another reason than Wayland. Anyway I'm using Pi now
That issue points out that it is probably a dependency problem.
The other problem is that they let a package manager block the UI and either swallow hard errors or unable to progress on soft errors. The errors are probably (hopefully) in some logs.
A dev oriented TUI should report unrecoverable errors on screen or at least direct you to the logs. It's not easy to get right, but if you dare to do it isn't rocket science either. They didn't dare.
I'm not a US citizen, so both companies are the same, as far as I'm concerned.
Still, I feel like "will commit illegal mass murder against their own citizens" is a significant enough degree more evil. I think lots of corporations will help their government murder citizens of other countries, but very few would go so far as to agree to murder their own (fellow) citizens ... just to get a juicy contract.
We also have taboos against betraying/murdering/whatever people of other tribes, but those taboos are much weaker and get relaxed sometimes (eg. in war). My point is, it takes significantly more anti-social (ie. evil) behavior to betray your own tribe, in the deepest way possible, than it does to do horrible things to other tribes.
This is just as much true for Russians murdering Ukranians as Ukranians murdering Russians, or any other conflict group: almost all Russians would consider a Russian who helps kill Russians to be more evil than a Russian who kills Ukranians (and vice versa).
But you're still choosing evil when you could try local models
https://www.washingtonpost.com/technology/2026/03/04/anthrop...
Many folks from other tools are only getting exposed to the same functionality they got used to, but it offers much more than other harnesses, especially for remote coding.
You can start a service via `opencode serve`, it can be accessed from anywhere and has great experience on mobile except a few bugs. It's a really good way to work with your agents remotely, goes really well with TailScale.
The WebUI that they have can connect to multiple OpenCode backends at once, so you may use multiple VPS-es for various projects you have and control all of them from a single place.
Lastly, there's a desktop app, but TBH I find it redundant when WebUI has everything needed.
Make no mistakes though, it's not a perfect tool, my gripes with it:
- There are random bugs with loading/restoring state of the session
- Model/Provider selection switch across sessions/projects is often annoying
- I had a bug making Sonnet/Opus unusable from mobile phone because phone's clock was 150ms ahead of laptop's (ID generation)
- Sometimes agent get randomly stuck. It especially sucks for long/nested sessions
- WebUI on laptop just completely forgot all the projects at one day
- `opencode serve` doesn't pick up new skills automatically, it needs to be restarted
- GH copilot API is a first class citizen with access to multiple providers’ models at a very good price with a pro plan - no terminal flicker - it seems really good with subagents - I can’t see any terminal history inside my emacs vterm :(
Even as a CC user I’m glad someone is forcing the discussion.
My prediction: within two years ‘model neutrality’ will be a topic of debate. Creating lock-in through discount pricing is anti-competitive. The model provider is the ISP; the tool, the website.
That is not the point. That is a mere technicality.
You signed a contract. If you don't ignore the terms of the contract to use the product in a way that is explicitly prohibited, you're abusing the product. It is as simple as that.
They offer a separate product (API) if you don't like the terms of the contract.
Also, if you really want to get technical: the limits are under the assumption that caching works as intended, which requires control of the client. 3P clients suck at caching and increase costs. But that is not the overarching point.
> Creating lock-in through discount pricing is anti-competitive.
Literally everyone does this. OpenAI is doing this with Codex, far more than Anthropic is. It's not great but players much bigger than Anthropic are using discount pricing to create an anti-competitive advantage.
And yet, OpenAI have publicly said they welcome OpenCode users to use their subscription package. So how are they being anti-competitive "far more" than Anthropic?
https://x.com/i/status/2034730036759339100
Reading through his X comments and GitHub comments he is behaving immaturely. I don't trust what he's saying here. Ripping out Claude API support was just throwing a tantrum. Weird given his age - he's old enough to be more mature.
There's also a request and a PR to add such option but it was closed due to "not adhering to community standards"
Curious how the context window management works in practice. With large repos, the "what files to include" problem tends to dominate — does it have a strategy beyond embedding-based retrieval, or is that the main approach here?
I wonder why did they use Typescript and not a more resource efficient language like C, C++, Rust, Zig?
Since their code is generated by AI human preferences shouldn't matter much and AI is happy to work with any language.
I really should look into more "native" Emacs options as I find using vterm a bit of a clunky hack. But I'm just not that excited about this stuff right now. I use it because I'm lazy, that's all. Right now I'm actually getting into woodwork.
[0] https://blog.gpkb.org/posts/ai-agent-sandbox/
IMO, the web UI is a killer feature - it’s got just enough to be an agent manager - without any fluff. I run it on my remote VMs and connect over HTTP.
There is nothing open about it. Please do not abuse the term "open" like in OpenBSD.
https://www.reddit.com/r/LocalLLaMA/comments/1rv690j/opencod...
?
> there isnt any telemetry, the open telemetry thing is if you want to get spans like the ai sdk has spans to track tokens and stuff but we dont send them anywhere and they arent enabled either
> most likely these requests are for models.dev (our models api which allows us to update the models list without needing new releases)
> opencode will proxy all requests internally to https://app.opencode.ai
> There is currently no option to change this behavior, no startup flag, nothing. You do not have the option to serve the web app locally, using `opencode web` just automatically opens the browser with the proxied web app, not a true locally served UI.
> https://github.com/anomalyco/opencode/blob/4d7cbdcbef92bb696...
Never tried it for much coding though.
OpenCode just has more bugs, it's incredibly derivative so it doesn't really do anything else than Codex.
The advantage of OpenCode is that it can use any underlying model, but that's a disadvantage because it breaks the native integration. If you use Opus + Claude Code, or Gpt-Codex + Codex App, you are using it the way it was designed to be used.
If you don't actually use different models, or plan to switch, or somehow value vendor neutrality strategically, you are paying a large cost without much reward.
This is in general a rule, vendor neutrality is often seen as a generic positive, but it is actually a tradeoff. If you just build on top of AWS for example, you make use of it's features and build much faster and simpler than if you use Terraform.
I only boot my windows 11 gaming machine for drm games that don’t work with proton. Otherwise it’s hot garbage
I do not understand the insistence on using JavaScript for command line tools. I don't use rust at all, but if I'm making a vibe coded cli I'm picking rust or golang. Not zig because coding agents can't handle the breaking changes. What better test of agentic coders' conviction in their belief in AI than to vibe a language they can't read.
At least you can easily turn off telemetry in Claude Code - just set CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC to 1.
You can use Claude Code with llama.cpp and vLLM, too right out of the box with no additional software necessary, just point ANTHROPIC_BASE_URL at your inference server of choice, with any value in ANTHROPIC_API_KEY.
Some people think that Anthropic could disable this at any time, but that's not really true - you can disable automatic updates and back up and reuse native Claude Code binaries, ensuring Anthropic cannot change your existing local Claude Code binary's behavior.
With that said, I like the idea of an open source TUI agent that won't spy on me without my consent and no way to disable it much better than a closed source TUI agent that I can effectively neuter telemetry on, but sadly, OpenCode is not the former. It's just another piece of VC-funded spyware that's destined for enshittification.
¹https://github.com/anomalyco/opencode/blob/4d7cbdcbef92bb696...
You'd be surprised how useless datasets become with like 10% garbage data when you don't know which data is garbage