Architecting Production-Grade Agentic AI: Multi-Agent Orchestration, Tool Governance, and Grounded Retrieval
A reference architecture for enterprise multi-agent systems: autonomous supervisor-worker orchestration, zero-trust tool…
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AI Insights
Practical writing on enterprise AI, generative AI, automation, evaluation and safe deployment.
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Building reliable agentic AI systems: tool sandboxing, state management, and loops
Autonomous AI agents require deterministic guardrails, structured memory, tool execution sandboxes, and loop-termination…
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How to evaluate agentic AI: step-level tracing, deterministic simulations, and trajectory scoring
Evaluating multi-step agents cannot rely on final output accuracy alone. Trajectory evaluation, tool call precision, and…
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Agentic RAG: routing, query rewriting, and multi-document synthesis in enterprise knowledge bases
Naive RAG fails on complex queries requiring cross-document comparison and multi-step reasoning. Agentic retrieval introduces…
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Multi-agent orchestration architectures: hierarchical supervisors versus peer choreography
Choosing between centralized supervisor routing and decentralized agent choreography dictates debuggability, token economics…
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Why most enterprise AI pilots never reach production
The gap between a convincing demonstration and a system people depend on is mostly unglamorous: evaluation, integration…
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