Start with work your team knows
Pull from historical fixes, difficult regressions, migrations, incidents, feature changes, and review corrections. Each case begins from a reconstructed repository state with explicit acceptance checks.
Product / Qualification
How do you evaluate coding agents on your own codebase?
Public leaderboards use someone else's tasks and setup. Fullbeam runs your current and candidate Stack Releases from the same repository state, with the same budget and acceptance policy, on work your engineers recognize.
What the release gate checks
The evidence behind the decision
Each result stays tied to the Stack Release, workload, repository state, and coverage that produced it. If evidence is missing, the gap remains visible in the release call.
Why should coding-agent evaluations use repeated runs?
Run high-value and high-risk cases several times. Fullbeam records pass-rate spread, cost spread, candidate-only failures, and invalid comparisons so one lucky trajectory cannot carry the release.
Keep engineering effort explicit
Qualification reports observed attempt cost per accepted-task equivalent. Steering, corrective turns, retries, CI recovery, reviewer changes, and rework are separate guardrails and remain unavailable when they are not joined to the comparison.
Decide one workload at a time
Promote where the candidate clears policy. Restrict the failure classes. Keep collecting evidence when coverage is thin, and roll back a canary when the production result breaks the original case.
Bring us the next stack change
A candidate can earn backend maintenance while staying away from database migrations. The release decision keeps that boundary intact.
One current releaseOne candidatePrivate repository workA workload-level decision