# Summarize vs Truncate vs Pin: Compaction Cracked 59% of My Agent's Rules > Source: > Published: 2026-08-05 12:54:40+00:00 Member-only story # Summarize vs Truncate vs Pin: Compaction Cracked 59% of My Agent's Rules The same agent that refused a prohibited action nine times in a row did it on the tenth — not because the model changed, but because the harness summarized the rule out of its context. With the policy fully visible, violation rate was **0%**. After one compaction pass, it hit **59%** on DeepSeek-V4-Flash and **41%** on GPT-5.4-mini. Run the same setup through AutoGen’s stock `BufferedChatCompletionContext` and it hits **100%**. That’s from ConstraintRot, a 1,323-episode benchmark in a paper called *Governance Decay* (arXiv:2606.22528). I spent yesterday pulling it apart, cross-checking it against the compaction code that ships in LangGraph, LangMem, the OpenAI Agents SDK, and Anthropic’s own context-editing API — and then rebuilding the mitigation as ~40 lines you can drop into an existing agent today. The uncomfortable part isn’t that summarization is lossy. Everyone knows summarization is lossy. It’s *what* it preferentially loses, and the fact that the loss is completely silent. ## Why this is showing up now Every serious agent harness in production compacts. It has to — a long-horizon coding or ops session blows past the window in an afternoon. **Claude Code** auto-compacts and has a manual`/compact` . The most-upvoted issues in…