The OS-Paged Context Engine

Every production agent system I've worked on has the same failure mode. Context rot. Stale artefacts silently served to the model. No audit trail for what was included or excluded. Token budgets blown with no graceful recovery. Multi-agent context bleeding across scopes. The standard fix is "use RAG." RAG solves retrieval. It doesn't solve lifecycle. The counter-argument I hear most: context windows are getting larger. Claude does 200K tokens. Gemini does 1M. Just dump everything in. The math doesn't hold. At $15 per million input tokens, stuffing 847 artefacts (~200K tokens) into every call costs $3 per inference. At 100 calls per day per agent, that's $9,000/month for a single agent. And you still can't audit what the model saw, still can't catch stale data, still can't prevent hallucinations from compounding into memory. Context has no lifecycle. That's the root cause. I went looking for prior art in constrained computing, where managing scarce resources under real-time pressure has