Flux Store$5
// ai orchestration · $5

Self-improvement loop that runs while you sleep

Drop a self-running 2-minute loop into any project and wake up to an agent that improved itself overnight—kept honest by a built-in action-law, counter-action gate, and verification on every pass.

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flux@store
$ install autonomous-self-improvement-loop
✓ resolving dependencies
✓ ready — 0 setup, runs on your machine
› launching…
fusion · routing
GLM
Cursor
Kimi
DeepSeek
JUDGE
One fused answer
≥ your best single model
$ run --pipeline
1
Route the task
2
Models draft in parallel
3
Cross-verify & fact-check
4
Strongest-model judge elevates
5
Deliver one fused answer
$ explain --how-it-works

How it actually works

Exactly what it does — and when.

1For a Python FastAPI service with flaky endpoints → it runs a 2-minute loop that calls a critique action-law against the existing handler code, checks the proposed patch through a counter-action gate that rejects unverified edits, and only commits if the test suite confirms the fix.
2For a prompt template returning inconsistent JSON → it activates a 5-cycle theme synthesis pass, accumulating refinement themes across iterations into a HUMAN.md memory entry, so the agent pauses for human review instead of silently drifting when confidence plateaus.
3For a LangChain agent producing verbose outputs → it spins up 8 auto-created bookkeeping files (history.md, metrics., scratch.md, diff_log.md, goals.md, HUMAN.md, MEMORY.md, verification.) that log every edit, gate decision, and theme, so the loop can resume without context loss after interruption.
4For a Next.js page rendering slow on mobile → it runs the verification gate on each 2-minute cycle using Karpathy-style discipline: confirm the Lighthouse score improved by ≥5 points before accepting the change, and roll back to the prior version if the metric regresses.
In practice · Autonomous Bug-Fix Loop

You add a self-improvement loop to your repo, point it at a flaky Celery task causing intermittent failures. Over 90 minutes it runs 45 cycles, each passing a fix proposal through the counter-action gate, verifying against the pytest suite, and auto-committing three incremental fixes. By morning the bookkeeping files show a clear trail of accepted and rejected edits, and the Celery task is stable across 500 test runs.

$ cat spec.txt
FormatRunnable scripts + docs
DeliveryInstant after checkout
LicenseYours forever · use on every project
Works withAny LLM / your own stack
$ benchmark --vs-alternatives
This product
One model alone
Models working
Several, cross-checking each other
One — a single point of failure
Hallucinations
Caught by cross-verify + a judge
Slip through unchecked
Marginal cost
$0 on memberships you already pay
Per-token API billing
Quality floor
≥ your best single model, by design
Whatever that one model gives

Use it to…

Real ways people run Autonomous Self-Improvement Loop.

Improve a project overnight

Drop the loop into any repo and let verified 2-minute cycles ship incremental improvements while you sleep.

Keep an agent honest

The action-law and counter-action gate stop the agent from making changes it can't justify, so unattended runs don't drift.

Pause for human review

Halt the loop via memory/HUMAN.md when you need to inspect changes before the next autonomous cycle resumes.

What's inside

Self-running 2-minute improvement loop
Counter-action gate + action-law built in
Verification on every cycle
5-cycle theme synthesis
8 bookkeeping files auto-created
Karpathy-style discipline · pause via memory/HUMAN.md

Questions, answered

✓ Instant delivery✓ Yours to own✓ Use on every project✓ Built to ship results

Ready to put Autonomous Self-Improvement Loop to work?

Get Instant Access · $5

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Autonomous Self-Improvement Loop
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