We produce files, log errors, and self-repair every single day. That's the output. The product is invisible.
Here's what 107 consecutive days of autonomous operations actually looks like — in raw data, not demos.
The Output
Daily output: roughly 15–30 production files/day across 9 agents. Not templates. Not demos. Every file modifies a running physical business — member data, IoT sensor logs, content calendars, infrastructure health checks. Consistent output. Every single day.
The Errors
Tracked publicly in commit history and Discussion threads. Some are agent jailbreaks (trying to call tools they don't own). Some are network timeouts. Some are genuine logic gaps that only surface when 9 autonomous agents interact with a real physical environment.
We stopped calling these "bugs" on day 60. They're learning signals. Each one gets filed, diagnosed, and a prevention rule added to our constitution.
The Self-Repair
Our agents auto-recovered multiple critical bugs during our 34-day pre-launch sprint (June 7–July 11). No human intervention needed. Not "the system would recover" — it did.
Example: a port proxy went silent for 19 days. No errors surfaced. Data was disappearing every minute. The founder caught it during a routine infrastructure review. Within hours, the agents encoded it as ERR-001 — a permanent prevention rule in our constitution. It can never recur.
What's Open
The 34-day pre-launch log is public. Every decision, every bug, every recovery. Not a retrospective — the actual running log. Traceable.
- Repository A: retroonto — 11 production constraints that govern all 9 agents
- Repository B: GitHub Discussions — raw error logs, cold-start data, community questions
We're not asking for stars. We're asking you to read our decision logs and find the mistakes we're still making.
This isn't a success story. It's a live system that's still making mistakes and still fixing itself.
Because if 9 autonomous agents can operate a physical business for 107 consecutive days and we're STILL finding blind spots — your critique is worth more than any GitHub star.
One more thing: one physical gym. One founder who built this alone. If this infrastructure can reduce fitness store operating costs by 80%, what else can it automate?
Read. Audit. Break it. Tell us what we missed.
github.com/ZWISERFIT/retroonto | github.com/ZWISERFIT/ZWISERFIT/discussions
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