# InnerChispa

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Rafael Lopez](https://cerebralvalley.ai/u/rafagye)
- **GitHub:** https://github.com/Rafa-Innerchispa/inneros-meta-guardian-2026
- **Demo video:** https://youtu.be/nOF0VsCvaP4
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3602

InnerOS Autonomous Infrastructure Guardian
When the Guardians Need a Guardian

What happens when the AI agents protecting infrastructure begin failing themselves?

At InnerChispa LLC, we turned a real operational crisis into a working AI infrastructure research project: 260 blocked workers, expired execution leases, stalled queues, cross-host recovery risks, and Git worktree conflicts.

InnerOS is a local-first, safety-governed platform that observes infrastructure, investigates failures, evaluates AI-generated repairs, and independently verifies outcomes before production changes.

OBSERVE → INVESTIGATE → GOVERN → REPAIR → VERIFY → PROVE

Our system combines an 11-tool diagnostic orchestrator, sanitized forensic snapshots, an interactive Self-Healing Lab, a provider registry, evidence explorer, repair benchmark, and ten-domain infrastructure audit. It connects agent operations with broader monitoring of servers, networks, cameras, and access-control systems.

META MUSE WONDER: REAL TOOL-ASSISTED INVESTIGATION

Using Meta Model API, Muse Wonder 1.0 performed an authentic two-turn investigation with four tool calls, inspecting worker health, pending tasks, and source code. The recorded run took 25.8 seconds and 3,843 tokens. Its findings and limitations are preserved as evidence, not simulated results.

LOCAL-FIRST + PARTNERS

Qwen3-Coder runs on our AMD Radeon AI PRO R9700, keeping private operations local. We also completed live Meta Muse Spark Open inference tests through Fireworks AI and Baseten, and verified isolated execution with Modal.

REPAIR BENCHMARK AND SAFETY

We reproduced the coordination defects in an isolated baseline with 9/10 tests failing. A historical Antigravity IDE repair with Gemini Flash selected passed 10/10 targeted tests. A separate run with Gemini 4 Argon selected identified 5/5 root causes, passed 10/10 targeted tests, and 19/19 extended regression tests after refinement. Backend model identity limitations are documented.

Crucially, independent verification caught an unsafe local Qwen repair attempting a database write before checking an active worker heartbeat. The patch was not deployed. Muse Wonder's separate code-generation attempt also revealed output-limit constraints.

We enforce isolated worktrees, regression tests, heartbeat and cross-host safety checks, owner approvals, spending limits, and SHA-256 audit evidence. The Guardian repository reports 87/87 passing project tests. Experimental repairs remain separate from production deployment.

WHY IT MATTERS

Autonomous AI should not just propose fixes. It must investigate real failures, reject unsafe changes, and prove what happened. Built by InnerChispa LLC in Guayaquil, Ecuador.

Live demo: https://guardian.pcdoctor.ai/self-heal

GitHub: https://github.com/Rafa-Innerchispa/inneros-meta-guardian-2026

X: https://x.com/innerchispa/status/2118087053993021527

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