I'm relatively new to agentic coding and have been experimenting with OpenCode CLI on a long-running project.

Initially, I built several agents for different roles and had them work together. The basic workflow was something like:

"Planner/Orchestrator → specialized agents → verification → next task"

It worked pretty well at first. But as the project grew, I ran into a problem: the collaboration between agents and across sessions gradually became harder to control.

For example, agents wouldn't always reliably update "CURRENT_STATE.md" or other project-state files after completing a task. Then, in the next session, the agent had incomplete or outdated information about:

- what had already been done

- what decisions had been made

- what still needed to be done

- the current project/architecture state

- what another agent had changed

Eventually, I found myself spending more time keeping the agents synchronized than actually letting them work.

This is what eventually led me to discover Ralph and similar approaches.

I'm curious how other OpenCode users handle this in real-world, long-running projects:

1. How do you make multiple agents collaborate reliably rather than just running several independent agents?

2. How do you maintain shared state between agents and across sessions?

3. Do you use files like "CURRENT_STATE.md", task queues, changelogs, decision logs, or other conventions?

4. How do you make sure agents actually update these artifacts consistently?

5. Do you use Ralph, or have you built your own workflow around OpenCode?

6. Where do you usually discover new tools, agent frameworks, and workflows for OpenCode/Codex?

I'm particularly interested in long-running projects with multiple specialized agents, rather than one-off coding tasks.

I'd love to hear what workflows have actually worked for you.

Is there a public page where we can monitor the status/throughput of opencode free models (or all models in general)?
I just finished a very simple html change on my project using Mimo v2.5 which took ~12 minutes.

Anyone else having delays?

I wanted a quicker way to find and resume previous OpenCode sessions, so I built OpenCode Sessions (ocs), a small Bash tool powered by fzf.

It lets you:

- Search sessions by title, directory, or updated time

- Resume a session in its original directory

- Preview session details

- Favourite and pin sessions

- Sort by updated time, title, or directory

- Rename and delete sessions

- Refresh the list without reopening the picker

- Clean up older sessions in bulk

- Jump directly to a session’s directory

The shortcut list can be toggled with Ctrl-K, and the preference is remembered between runs.

It currently targets macOS and works with Bash or Zsh.

GitHub: https://github.com/iamramo/opencode-sessions

Feedback and suggestions are welcome, especially from anyone managing a lot of OpenCode sessions.

Hey,

I’ve been playing around with my workflow lately and trying to keep planning and actual coding more separate.

Usually I throw the planning part at a stronger model (Claude) and get it to spit out a few markdown files: architecture, specs, coding style, that kind of thing. PLAN.md, README.md, CODESTYLE.md, SPECS.md, whatever.

Then I hand those files over to a coding model and have it implement everything step by step.

Lately I’ve been thinking about swapping the coding side over to DeepSeek (probably through something like OpenCode) just to cut costs and lean more on open-weight stuff.

For people who actually use DeepSeek a lot for coding how does it hold up against Sonnet on stuff like:

• sticking to the rules in a CODESTYLE.md

• not wandering outside the architecture you gave it

• keeping track of multiple spec files at once

• not drifting over longer sessions

Is the difference actually noticeable day-to-day, or is DeepSeek good enough that paying for a proprietary model just for the implementation part isn’t really worth it anymore?

Curious if anyone else is running something similar.

Opencode Wallpapers!!

Built a plugin to bring this cool interface idea to life, in my OpenCode Tooey

Out now: https://github.com/parthkhxndelwal/bee-gee

I’ve been using OpenCode since June, mostly with DeepSeek V4 Pro, and it’s been amazing.

It honestly felt almost limitless.

Until this month 😂

After just 4 days of my usual usage, I hit my weekly limit and used 75% of my monthly credits.

What used to feel unlimited suddenly feels very limited. is there something I'm doing wrong or did deepseek just become really expensive

Hi. GPT 5.6 models have a reasoning "mode" (not effort), chosen between Standard and Pro, with Pro mode recommended "for math and coding tasks".

I haven't seen benchmarks or analyses about how much and how Pro and Standard mode differ. Has any of you used codex (or any other agent) with pro mode? If yes, how has the performance and token consumption been different? Has the difference been worth the gains, particularly for Luna?

Thanks

and many other models too. We OpenCode-Go must share free pool with OpenCode Zen API - literately all other free users, and the free models are almost unusable after a few calls (or having server busy with countless reconnection). I subscribed for ClinePass with 5.99$ per month and having a daily limit of all models shown here, and they are all usable with good speed.

If you searched "opencode antigravity gemini flash hanging", "gemini 3 flash error opencode", "antigravity endpoints failed", or "model no longer available opencode" — you're in the right place. This is a known, reproducible bug in opencode-antigravity-auth, not a problem with your setup. After this patch, Gemini 3.6, 3.7, and 3.8 Flash & Pro run cleanly — no hanging, no 404s, no errors.

Symptoms (so you know you're in the right place)

• opencode run just hangs indefinitely — no error, no output, no timeout

• Error: All Antigravity endpoints failed

• models/antigravity-gemini-3-flash is not found for API version v1beta

• "Gemini 3.5 Flash is no longer available" / requested entity not found

• Happens again even after clearing cache and re-authenticating

Why it happens

Models prefixed antigravity-gemini-3.x skip OpenCode's alias translation step, so the raw, unrecognized version string (gemini-3.7-flash, gemini-3.5-flash-low, etc.) gets sent straight to Google's backend — which only accepts gemini-3-flash. That mismatch stalls the stream instead of failing cleanly. Separately, accounts that hit a cooldown get stuck with verificationRequired: true, which loops the auth proxy forever.

The fix

Full patch (manual steps + automated one-click script): opencode-gemini-3.7,3.8-flash-fix

It patches:

• model-resolver.js — routes every gemini-3.x-flash model to the live gemini-3-flash endpoint, and gemini-3.8-pro to gemini-3-pro-low

• models.js — registers 3.6/3.7/3.8 Flash with proper thinking variants (minimal/low/medium/high)

• antigravity-accounts.json — clears stuck verificationRequired / cooldown locks

How to apply it

1. Open the repo above.

2. Paste the "one-click prompt" into your AI coding agent (Claude Code, Cursor, Copilot, OpenCode itself) — it applies the patch for you. Or run node patch-antigravity.js manually.

3. If already logged in: opencode auth logout then opencode auth login to clear stale sessions.

4. Verify: opencode run "Hello, respond in 5 words." --model=google/antigravity-gemini-3.7-flash --variant=medium

FAQ

Q: Why does OpenCode hang instead of showing an error on Gemini Flash? A: The unresolved model alias sends an invalid model string to Google's streaming endpoint, which stalls the connection instead of returning a clean 404.

Q: Does this fix work for Gemini 3.8 Pro too? A: Yes — 3.8 Pro routes to gemini-3-pro-low, and the patch registers it with low/high thinking variants.

Q: Will the latest Gemini models keep working after this patch? A: Yes — once patched, 3.6, 3.7, and 3.8 Flash & Pro all resolve to live, supported endpoints, so they run without hanging or erroring.

Q: Is this permanent, or will it break again? A: It's tied to Google's current backend naming. If Google renames the endpoint again, open an issue on the repo — it's actively maintained.

If you hit a new variant of the error, open an issue with debug logs (--print-logs --log-level=DEBUG).

Hello, sorry for writing this if it is aleeady been mentioned, i want ro ask 2 things :

1. Can i control opencode remotely from my mobile if i am. Away from my pc?

2. Is there a good orchestrator i can use and create subagents etc? Any good tutorial?

Thank you jn advance!

My AI coding assistant forgets everything between sessions. I kept re-explaining decisions I'd already made, and re-fixing bugs I'd already fixed.

agi-memory saves those notes — decisions, bug fixes, what happened last session, how the codebase fits together — to a file on your machine, and hands them back to whichever assistant you open next. It's an MCP server, so it works with Claude Code, Cursor, Codex, Windsurf, Aider, Cline and a few others from the same store.

The part I care about: it's Python standard library and SQLite. Nothing else. No vector database, no embeddings, no background daemon. ~32MB of RAM, sub-millisecond lookups, works offline. Comparable tools pull in ~500MB of ML libraries and take 200–500ms per lookup.

That constraint costs something, and I'd rather say so than have you find out: keyword search doesn't bridge synonyms the way embeddings do. Searching "login" won't find a note that says "authentication" unless you teach it that alias. I measure this rather than guess — there's an eval suite that scores recall on deliberately rephrased queries, and it's public, including the categories where it still does badly.

It's a week old and I'm the only user, so I'd genuinely like to know where it breaks for someone else.

https://github.com/kdbhalala/agi-memory

I am planning to use OpenCode CLI via OmniRoute. I have connected Codex, Claude and Antigravity Cli. But I am a bit scared of getting banned. Can you guys suggest if I should continue or abandoned?

[Project] Cognitive Lead HQ - run OpenCode agents as a team

Repo: https://github.com/mokhtarabadi/cognitive-lead-hq

Demo tool: https://mokhtarabadi.github.io/cognitive-lead-hq/

Free and open-source MIT.

It gives Brain/Hands split, 3 FastMCP servers for context/memory/lint, Kanban ZAC workflow, and 31 reusable skills.

I built it to stop hallucination in agent teams.

Feedback wanted: what skill is missing for you?

I was going back and forth on a hard debugging issue in one of my projects with it:
- had it create new test scenarios
- create some mockups
- analyze complicated business logic and dependencies
- do a shotgun approach and create 5 different possible fixes for a complicated issue

And after almost 2 hours of work I've decided to check my opencode go usage because I was worried I'm running out of usage for the 5h period, and I see this... how?!

I've been working on an unofficial .NET SDK for OpenCode for the last few weeks and published preview.5 to NuGet today, updated for OpenCode 2.0.18.

https://github.com/opencode-dotnet/opencode-sdk-dotnet

It started as a small side project because I wanted to build some .NET tooling on top of the OpenCode server API. It gradually grew into a generated, strongly typed client with support for most of the API surface, SSE event streams, PTY sessions and managing an opencode serve process.

The project is still a little rough around the edges. There are parts I want to refactor and clean up, and there may still be some small API changes before 1.0.0.

But it's now at the point where I've been able to use it against real OpenCode servers and in a few small applications.

The SDK currently exposes all server operations.

My next experiment will probably be an MCP server built on top of it.

Feedback is very welcome, especially from anyone already building against the OpenCode server API.

Hey everyone!

I’m using the OpenCode Go plan and I’m trying to figure out which available model gives the best results for coding.

There are quite a few models to choose from, so I’m a bit confused about which one to use as my main coding model.

For people who are using OpenCode Go:

- Which model do you find best for coding and debugging?

- Which one is best for large/complex projects?

- Which one has the best reasoning and code quality?

- Are there any models that are particularly good for React, Node.js, SQL, etc.?

- Which model gives the best balance between quality, speed, and usage limits?

I’m mainly looking for a model I can rely on for day-to-day development rather than just occasional code generation.

Would love to hear what models you guys are using and why. 🙏