Agent Session Evidence for AI Coding Teams

Direct answer

Agent session evidence is the set of facts that proves what happened during an AI agent run. For coding teams, that means command classes, file scope, diff narrative, test outcomes, exception handling, and the receipt that can be shared with a reviewer or client.

Where it fits

• Multiple agents work across repositories and the team needs consistent evidence per run.
• A client wants proof of delivery without access to private developer chat context.
• An engineering manager wants to compare session risk across projects.

Operational steps

1. Normalize evidence inputs from terminal logs, agent summaries, and git diffs.
2. Classify commands and attach test proof, coverage, lint, or smoke checks.
3. Create a readable receipt with both product and security summaries.
4. Use retention controls so evidence lives only as long as the project requires.

Common risks

• Evidence that is too raw can leak context; evidence that is too thin is not credible.
• Agents may perform network or write actions that need explicit exception labels.
• Teams need consistent evidence formats across Codex, Claude Code, and other agents.

How SandboxReceipt AI helps

SandboxReceipt AI gives agent sessions a consistent evidence format across command audit, sandbox report, and client receipt workflows.