Search topic: AI agent harness
AI agent harness architecture
Definition, components, execution protocol, controls, and a production implementation path.
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Build AI agents that survive production
Start with the problem you need to solve. Each topic below has one primary guide, then narrower implementation references. This is the shortest path through the ContextOS library.
Search topic: AI agent production readiness checklist
AI agent production readiness
A practical checklist for context, tools, identity, policy, evaluation, replay, and operations.
Read the primary guideSearch topic: AI agent evaluation framework
AI agent evaluation and scorecards
Datasets, policy and utility checks, release gates, production slices, and regression replay.
Read the primary guideSearch topic: AI agent memory architecture
AI agent memory architecture
Working, episodic, semantic, procedural, and organizational memory with governed promotion.
Read the primary guideSearch topic: AI agent security best practices
AI agent security and authorization
Prompt-injection boundaries, scoped identity, approval modes, tool authorization, and audit evidence.
Read the primary guideSearch topic: MCP security
MCP security for production agents
Capability manifests, schemas, authorization, approvals, idempotency, observability, and replay.
Read the primary guideSearch topic: context engineering for AI agents
Context engineering for production AI agents
Versioned context assembly, evidence selection, token budgets, policy, and replayable compilation.
Read the primary guideSearch topic: multi-agent orchestration architecture
Multi-agent orchestration architecture
Specialist lanes, bounded delegation, durable sessions, authority, and final decision ownership.
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