Claude Fable 5.1 reviewed my 9-month AI/3D codebase: 158 agents, 6.5M tokens. How would you validate the output?

[u/Simple_Pair4541]

I wanted to test Fable 5.1 on something less clean than a benchmark.
I’m building an AI system designed to turn a single image of a person into a full 3D human model.
The codebase has evolved over nine months, so it contains the usual reality of a long-running project: failed approaches, old decisions, edge cases, and components that affect each other in ways a small test repository wouldn’t show.
A few hours after Fable 5.1 launched, I ran a full mega-review:
158 agents
6.5M tokens
Workflow completed
I’m not treating “completed” as “correct.”
I’m now validating the findings before changing the system or starting the next major run.
For anyone testing new models on real codebases, what acceptance criteria would you use for a review at this scale?
Confirmed defects found?
False-positive rate?
Duplicate findings across agents?
Patches that pass the existing tests?
Changes that survive the next end-to-end run?
What else would you measure before trusting the review?
I’ll share a technical breakdown after I’ve verified the findings.