Agentic AI Is Distributed Systems
Every agentic pattern has a distributed-systems ancestor. Part 1 maps the lineage; Part 2 builds a playbook for semantic correctness.
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Agentic AI Is Distributed Systems. Part 1: The Map Every AI Engineer Should Have Memorized
Every major agentic AI pattern has a named distributed systems ancestor going back decades. MoA is ensemble computing. ReAct is a control loop. AutoGen is the actor model. LangGraph is a workflow engine. Multi-agent coordination is a blackboard system. This article maps each AI concept to its CS lineage, explains what that means for engineers building today, and names the three problems that genuinely have no distributed systems precedent — the real frontier where new thinking is required.
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Agentic AI Is Distributed Systems. Part 2: Building on Uncertain Ground — Practical Semantic Correctness for Agentic Systems
You cannot mathematically prove an LLM correct. But you can architect around it. Part 2 surveys the three research communities approaching semantic correctness for LLM outputs — formal verification, runtime guardrails, and post-condition verification — maps their results honestly, and delivers a concrete engineering playbook: four patterns engineers can implement today to build agentic systems that fail visibly, recover gracefully, and escalate correctly.