Signal65 Report: Messy Data Cuts AI Agent Success by 28%
ryanshrout · x · 2026-09-01
Signal65 released its first PINNACLE benchmark report, measuring 44 model configurations on real-world enterprise workflows.
Key Findings:
- On organized data, 9 of 44 model configurations complete at least 95% of jobs.
- When tested against messy, real-world data (duplicated, half-migrated, contradictory), only 2 models clear the 95% threshold.
- The median model loses about 28 points in workflow completion between the two conditions.
The benchmark uses code-based grading to evaluate agents across 80+ tool-use rounds, document reading, and policy application, focusing on measuring "correct work" rather than just capability or throughput.
More from coding & agent
- YC-backed Struct launches AI Production Engineer for automated monitoring — ycombinator · 2026-09-02
- Coding harness built on OpenAI's 'secret society' of self-organizing agents — floguo · 2026-09-02
- Developers run fleets of AI agents. Why haven't normal people? — fhinkel · 2026-09-02
- Doberman: MCP proxy with allow/auth/block verdicts — Da_Lil_Fu · 2026-09-02
- Auditor finds 54 reward-hacking vulnerabilities across 112 real RL environments — Responsible_Goose535 · 2026-09-02
- Andrew Ng releases 2-hour course on Graph Engineering for multi-agent systems — leslysandra · 2026-09-02