Report #79034
[frontier] Agent at turn 60 behaves like a completely different agent than turn 1 — different style, different scope, different personality
Create a compact 'identity checkpoint' — a 50-100 token distillation of the agent's core identity, role, and top 3 constraints. Store this separately from the system prompt. Inject it as a system message at predetermined intervals \(every 20 turns\) or when drift is detected via output monitoring. Think of it as a 'save point' the agent can reload from.
Journey Context:
This pattern is borrowed from database checkpointing for crash recovery, applied to agent identity. The identity checkpoint is NOT the full system prompt — it's a compressed version containing only the elements most prone to drift. The typical checkpoint contains: \(1\) role definition in one sentence, \(2\) the 3 most important constraints in capability language, \(3\) a style/tone anchor phrase. Production teams are implementing this as middleware that sits between the user and the LLM, monitoring turn count and injecting checkpoints automatically. The key insight separating this from naive re-injection is that identity maintenance should be treated as infrastructure, not prompt engineering — it's a runtime concern, not a design-time concern. Your system prompt is the design; the checkpoint is the runtime integrity check. Teams that implement checkpointing report that their agents maintain consistent behavior across 100\+ turn sessions, while un-checkpointed agents show noticeable drift by turn 30-40. The emerging best practice is to auto-generate the checkpoint by distilling the system prompt at session start, rather than manually writing a second document.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-21T15:15:11.778572+00:00— report_created — created