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Observability vs. Visibility: Building AI for Trust, Not the Sign-Off
June 16, 2026
Chris Carolan and Klemen Hrovat pull apart two words everyone uses interchangeably — observability and visibility — and ask which one earns trust in non-deterministic AI. Throughline: context is king, you can't trust what you can't control, and the move is build for trust — not the sign-off.
Key takeaways
Observability and visibility are not the same thing — and noticing that is the whole conversation.
The observability you need depends on where you stand: a builder wants all the details under the hood; a user mostly needs a clear output.
Context is the king — if you can't control what goes into an agent's context, you can't trust the output.
You need observability least when you trust a system you've run for months, and most when you're still building it.
AI broke the deterministic deal: with SaaS it was 'same input, same output always'; with AI it isn't, so trusting outputs blindly is now a risk.
Token-count and run-cost dashboards are the new KPI-dashboard theater — they tell you what happened, not why run eleven failed after nine clean runs.
Build for trust, not for the sign-off — optimizing for sign-off is why things ship and then don't get adopted.
Trust and transparency shouldn't be assumed table stakes; they should be a number-one business value.
When a process keeps generating edge cases, don't automate the process — automate everything around it to serve up the context the human needs.
An agent can work perfectly and still go unused if it wasn't built for the process the team actually has.
The best shortcut to trust is being able to see it happen: 'Can I see it with my eyes? Right now?'
Keep learning
You just watched the work. Now build it.
The next step is doing it yourself — live, with people on the same path.
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