show me the your loops that build features
Matthew Berman requests software feature-building loops, prompting Peter Steinberger to note they require clearly specified target issues
The exchange highlights operational constraints in agentic coding workflows.
Many users shared practical examples of AI loops with cheap models for feature building because they cut cycle times, survive refactors, and enable efficient agent workflows.
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@steipete Have you built features with loops?
Will show you how to setup loops in return.

@MatthewBerman Summary if you want to make a video 🙌

@MatthewBerman mine, from today, fully public: spec → plan → fresh subagent per task on cheap models → two adversarial reviews per task on the big one → merge at green.
9 hours, 30 subagents, 13 PRs merged.
the loop shipped the fix for its own routing: http://ax.necmttn.com/s/Necmttn/36d340286c8d43d1d68d9e5e0e36f2fc
@MatthewBerman if the issue is clear and specified, yah
@steipete Have you built features with loops?

@MatthewBerman /goal Please implement PROBLEM_STATEMENT. See linux, xnu, and llvm-project directories to ground yourself. I want performant and easy to read LLVM IR complete with unit/integration tests and profiling benchmarks. Pay special attention to cache use and IO overhead.

@MatthewBerman

@MatthewBerman I missed some updates Matt #spacex just sold my house, my wife doesn’t know
@steipete Can you provide an example? I’m trying to put together some educational content on loops
@MatthewBerman if the issue is clear and specified, yah

@RXed_EU @MatthewBerman Just tell her......

@goldenelephant1 @MatthewBerman She’s a lawyer, lawyers don’t believe in aliens @CarloDAngelo right?

@MatthewBerman here is how it looks

@MatthewBerman I would only use "loops" on a self hosted/local AI model.

@MatthewBerman is it just me, or are loops overkill for day-to-day dev? I find myself quite happy with a strong planning skill and execution skill.

something i've been playing with:
have all your feature requests and communications (email, teams, etc) added as issues on the github repo.
Every 30 minutes, an orchestrator on codex delegates new issues to one codex thread.
The thread works on that issue, updates on the github issue, opens a PR, and if it needs your feedback, comments on github for your approval.
you write your feedback on github and the orchestrator will pcik that up when it runs again to reinvokes the codex thread assigned to that issue to handle my response.
Once a feature or bug merged, the agent validates it with tests and a QA user journey, posts screenshots on the issue for your review, then you can close the issue.
Your job is basically reviewing github comments.

@MatthewBerman

@MatthewBerman We are building them now for lemmebuyit and skill sets on the MCP server.

@MatthewBerman sorry, no. proprietary knowledge. 😆

@MatthewBerman 10 PRINT "CREATE SLOP" 20 PRINT "BURN TOKENS" 30 GOTO 10 RUN

@MatthewBerman Squirrel!

@MatthewBerman Have quite a few… the one I like best is how to set up tools in @LangChain has reduced cycle time dramatically