DP

DepthPilot AI

System-Level Learning

What This Path Builds

Check whether the samples come from real failures.
Check whether version comparison and pass criteria are explicit.
Check whether the result changes launch or rollback decisions.

Why This Topic Matters

Step one: inspect the sample source

If the samples are detached from real usage, strong metrics still do not prove the system improved.

Why This Topic Matters

Step two: inspect the comparison design

You need version comparison and pass criteria. Otherwise you are staring at numbers you cannot interpret.

Why This Topic Matters

Step three: inspect whether the eval affects decisions

A good eval checklist must end in launch, rollback, or prioritization, not just a report.

Questions Learners Usually Ask

How is this different from a normal checklist?

It is not a project-management checklist. It is a decision checklist focused on whether AI evaluation is actually valid.

Do solo builders really need a checklist?

Yes, even more so. Teams can correct each other, while solo builders are easily misled by vague improvement feelings.

An AI eval checklist for deciding whether the system actually improved | DepthPilot AI