Articles
Building Effective AI Agents
Anthropic's own engineers stepping back from the hype to draw a precise line between a "workflow" (LLMs and tools wired through code you control) and an "agent" (the model deciding its own next steps) — a distinction that matters the moment you're deciding how much autonomy to actually hand an LLM in production. The five patterns it lays out — prompt chaining, routing, parallelization, orchestrator-worker, evaluator-optimizer — are the ones I keep coming back to when scoping an AI feature, because they're composable primitives rather than a framework you have to buy into. Worth reading before you reach for a heavyweight agent framework: most production use cases turn out to need a workflow, not an agent.