03LABORATORY

AI Reliability Observations

EXPERIMENT · AI Systems

A sample experiment on how small reliability mistakes compound inside agentic workflows.

OBJECTIVE

What failures show up first when an AI workflow has to be repeated.

HYPOTHESIS

A small workflow sketch and note-taking pass over the points where the process drifted.

METHOD

The clearest wins came from making the failure modes visible early.

RESULT

A tiny amount of process ambiguity can create a large amount of output noise.

FAILURE

The system became hard to reason about when too much was hidden in assumptions.

Trim the workflow until the handoffs are obvious.

This sample lab entry records a simple observation: reliability is often a design problem before it is a scaling problem.