I have been asking agent builders what they want in a run receipt after an AI agent finishes a...
Run receipts for AI agents need five fields instead of transcripts—resume_verdict, claimed vs verified, assumptions, tried and reverted, programmatic evidence—enabling safe resume and hand-off decisions. For multi-agent workflows, explicit verification boundaries prevent inheriting unproven claims and duplicate failed approaches.
I have been asking agent builders what they want in a run receipt after an AI agent finishes a task.
The answers were better than my original schema.
The common theme:
A receipt should not be a transcript summary. It should help someone decide whether the run can be trusted, resumed, reverted, or handed to another agent.
Here are the five fields that kept coming up.
Most AI agent demos optimize for the first successful run. Real agent work gets interesting after...
Most AI agent demos optimize for the wrong screenshot. They show the moment where the agent produces...
I have been writing here about one core idea: AI agents do not only fail because they forget...
When an AI agent fails in production, the first instinct is usually to tweak the prompt and rerun the...
A short note on why coding agents need budgets, verification, and receipts.
A hands-on demo of cryptographically verifiable agent behavior — a tamper-evident receipt proving an agent ran the approved…
