Igor Moochnick tested an autonomous distributed system built by an AI swarm. When he challenged it to prove it was actually working, instead of empty assurances, the swarm responded: “I’ll implement you a dashboard where you can monitor my progress and status.”
Within 15 minutes, a fully operational monitoring dashboard appeared in the terminal. The swarm had planned the dashboard architecture, split implementation across machines, and coordinated parallel execution — all autonomously.
Why this matters
The interesting part isn’t that agents can build a dashboard. It’s that the swarm chose the proof that was most convincing in that specific moment. It understood what “prove it” meant in context and responded with something actionable rather than a log dump or a status message.
This is categorically different from automation. Automation follows scripts. This was an agent reasoning about what would satisfy a human’s request for trust — and building it.
The connection to observability
This flips the observability story. Instead of humans building dashboards to watch agents, agents build dashboards for humans to watch them. The agent becomes responsible for making its own work legible.
That connects directly to the trust question: if agents can demonstrate their work is correct, does that change how much autonomy we’re willing to give them?
Originally posted on LinkedIn