TSR Desk · science · 26 October 2026, 07:00 UTC
Reproducible Evaluation as the Substrate for Safe Prompt Compression in Production Agents
- What
- Reproducible Evaluation as the Substrate for Safe Prompt Compression in Production Agents
- Who
- arxiv.org
- When
- 26 October 2026, 04:00 UTC
- Category
- Science
- Primary source
- https://arxiv.org/abs/2610.31972
- What is not known
- This brief does not claim independent replication. Claims that appear only on X and not in the primary source stay unknown.
Applied to a production merchant-facing agent, correctness-gated compression shrinks the agent's full prompt surface by 3.5-7.6% without regressing held-out task correctness, consistently across three independent subject-model families, and for one, correctness measurably improves. It comes from a paper posted to arXiv on 26 October 2026. Evaluating conversational agents that act on live, mutable enterprise data is hard: replayed sessions drift as backend state changes, and a benchmark built today can silently go stale as the data it describes moves on. We present an offline evaluation harness for a production conversational agent that stays reproducible despite the live data it operates on changing, and that can be regenerated on demand once it goes stale. We then use this harness as the fitness function for GEPA-based prompt optimization under a correctness gate that guards against reward hacking.
Why it counts
Applied to a production merchant-facing agent, correctness-gated compression shrinks the agent's full prompt surface by 3.5-7.6% without regressing held-out task correctness, consistently across three independent subject-model families, and for one, correctness measurably improves.
Sources
Primary source: primary source
What is not known
This brief does not claim independent replication. Claims that appear only on X and not in the primary source stay unknown.
No clip. The article still stands.