Five criteria of good context for AI agents
A 2026 paper formalizes five criteria for good AI agent context: relevance, sufficiency, isolation, economy, and provenance. Here's how to design for each.
Further reading
Articles about Epistemic Provenance
5 articles from the Wire blog, sorted newest first. Return to the Epistemic Provenance definition for context.
Claude Opus 4.8 hallucinates less by answering less
Claude Opus 4.8 tops a hallucination benchmark without getting more accurate. It learned to abstain. Why retrieval honesty is a context engineering win.
When agent memory needs sleep, and when it doesn't
Memory consolidation fixes one specific failure: agents writing the same claim dozens of times into a flat scratchpad. When it helps and where it breaks.
Anthropic's Managed Agents memory: what it changes
Anthropic launched Memory for Managed Agents on April 23, 2026 in public beta. What the design means for agent scope, freshness, and context engineering.
Provenance is a context engineering primitive, not a trust score
Retrieval provenance for AI agents isn't an audit log or a trust verdict. It's structural metadata (source, position, time, edges) agents use to plan.
Put context into practice
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