Topic starter
18/08/2026 2:36 pm
TL;DR: Compaction can silently erase in-context agent policies, turning long-horizon AI systems into governance drift machines, according to TruFoundry’s analysis of recent research on governance decay. The operational lesson is that compliance and blast-radius controls must live outside the context window, because anything inside it can be summarized away.
Editorial analysis by NHI Mgmt Group, based on content published by TruFoundry: “Governance Decay, Explained: How Context Compaction Erodes Agent Policy — and Where Enforcement Belongs”.
Key questions
Q: What breaks when agent policies live only in the context window?
A: The control breaks when compaction or eviction removes the rule that was supposed to constrain the agent.
Q: Why does governance decay create a compliance risk for AI agents?
A: Because compliance rules, data boundaries, and approval requirements can disappear during routine summarisation even when the task continues normally.
Q: How can security teams tell whether an agent is failing because of compaction?
A: Look for behaviour changes that line up with transcript compression, summarisation thresholds, or memory eviction rather than with a new prompt, model version, or user request.
Practitioner guidance
- Move high-consequence policies out of context Put data egress limits, tool scope, approval thresholds, and spend rules on an external enforcement path that compaction cannot rewrite.
- Classify in-context rules as steering only Reserve prompts and memory for tone, task framing, and low-risk preferences, then document which controls are not acceptable to keep only in the transcript.
- Instrument compaction as a governed event Log when history is summarised, what policy text survives, and when behaviour changes around a compaction boundary so investigators can distinguish forgetting from injection.
Bottom line: Governance decay is a control-placement problem, not just a prompt-design problem, because compaction can silently remove the very rules that agents were following.
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18/08/2026 3:21 pm
Governance decay is an enforcement placement problem, not a prompting problem. Once a control can be summarised away, it is not a durable control. That is true whether the rule governs data egress, tool scope, or spending. For agentic AI programmes, the decisive question is not how elegantly the policy is written, but where it lives and whether compaction can reach it.
A few things that frame the scale:
- AI-related credential leaks surged 81.5% year-over-year in 2025, with the surrounding AI infrastructure leaking 5x faster than core LLM providers, according to the State of Secrets Sprawl 2026.
A question worth separating out:
Q: Should agent governance be enforced in prompts or at the gateway boundary?
A: Use the gateway boundary for controls that cannot be allowed to vanish, such as outbound data restrictions, tool permissions, and budget limits. Keep prompts for steering, not for enforcing the controls that must survive compaction. The clean split is durable enforcement outside the context and conversational guidance inside it.
👉 Read our full editorial: Governance decay in AI agents shows where policy enforcement belongs