Verification is the difference between a workflow that feels smart and a workflow that ships reliably.
Claims should be backed by evidence proportional to the risk of the change.
For documentation-heavy work, verification usually means:
- links resolve
- file paths are real
- the structure is coherent
- examples match the documented model
For executable work, verification typically expands to:
- diagnostics
- targeted tests
- builds
- manual sanity checks
When a workflow depends on production reality, local confidence is not enough.
That is when runtime signals, issue trackers, logs, traces, or tools like Sentry matter.
- What evidence do I have right now?
- Is it local evidence or runtime evidence?
- What could still be wrong even if the docs or tests look clean?
- Am I reporting certainty or just momentum?
AI accelerates drafting. It also accelerates plausible mistakes.
Verification is how you keep the speed while reducing self-deception.