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.
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).
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]:
> 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 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.
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.
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.
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.
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 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!
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.
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.
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.
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.
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.
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).
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.
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.
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.
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.
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)
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.
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.
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’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.
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).
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
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 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
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.
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'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.
- 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 :(
One thing that makes coding agents really useful is structured data access via MCP servers. Instead of the agent trying to scrape a webpage to understand your project's context, you give it a direct API to query structured data from 9+ sources (GitHub repos, Stack Overflow questions, arXiv papers, npm packages).
The biggest bottleneck I've seen isn't the coding — it's the agent not having enough context about the ecosystem it's working in.
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!
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
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 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)
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.
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 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.
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.
[1] https://opencode.ai/docs/config/#precedence-order
[2] https://github.com/anomalyco/opencode/issues/10939
[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
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.
OpenCode has been much more stable for me in the 6 months or so that I’ve been comparing the two in earnest.
https://x.com/thdxr/status/2031377117007454421
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.
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?
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.
[1] https://github.com/badlogic/pi-mono/tree/main/packages/codin...
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.
https://www.youtube.com/live/z0JYVTAqeQM?si=oLvyLlZiFLTxL7p0
https://github.com/Vibecodelicious/opencode
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
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.
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.
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.
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 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.
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 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.
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
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
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.
- 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 biggest bottleneck I've seen isn't the coding — it's the agent not having enough context about the ecosystem it's working in.
Hugely grateful for what they do.
There's also a request and a PR to add such option but it was closed due to "not adhering to community standards"
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
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...
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)
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.
Never tried it for much coding though.
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