IDKMesh is an open-source research and engineering project for verification-first coordination of humans, AI agents, software tools, and heterogeneous compute. This topic hub answers the practical questions people ask when they need autonomous or semi-autonomous agents to produce work that can be checked, traced, and integrated safely.
The repository remains the canonical source of truth. These topic pages are discovery guides: they connect common search questions to the relevant contracts, architecture, experiments, tools, and evidence already maintained in IDKMesh.
| Topic | Use it when you are asking… |
|---|---|
| AI agent verification | How do I verify an AI agent’s output instead of trusting its own success claim? |
| Multi-agent orchestration | How should multiple agents decompose, coordinate, and hand off bounded work? |
| AI code review | How do coding agents create pull requests without becoming their own reviewers or merge authority? |
| LLM-as-a-judge reliability | When is an LLM evaluator reliable, and what should be measured before using one as a judge? |
| Verifier panels | Why can a panel of many reviewers contain far fewer independent votes than its head-count suggests? |
| Agent governance | Where should human approval, permissions, and integration authority sit in an agentic workflow? |
| Provenance and evidence | How do I bind claims to artifacts, identities, checks, and reproducible evidence? |
| MCP and A2A interoperability | What roles do MCP and A2A play, and where does IDKMesh add coordination/evidence semantics? |
| Verification scaling | What happens when generation grows faster than review and verification capacity? |
| Verified swarm engineering | What would an open, Git-native, verification-first framework for collaborative agents look like? |
Across all ten topics, IDKMesh uses the same authority boundary:
bounded goal
-> Work Unit
-> worker attempt
-> untrusted candidate + ResultManifest
-> verifier-owned evaluation
-> VerificationResult + evidence
-> explicit human/governance integration decision
The important separations are simple:
Last reviewed: 2026-09-23.