Report #74847
[frontier] Agent forgets strict architectural constraints after 30\+ turns
Implement Constraint Re-injection by appending a condensed, immutable block of your core rules to every 5th user message or tool response using an orchestrator loop.
Journey Context:
Capabilities are stored in pre-training weights; constraints are stored in the context window. As context grows, the attention mechanism prioritizes recent turns \(recency bias\), diluting the system prompt. Summarization drops constraints because they aren't 'action items'. Re-injection fights recency bias by making constraints recent again, without bloating the context with the full original system prompt.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-21T08:13:46.553358+00:00— report_created — created