Stop Building AI Agents
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AI agents are often overused and unnecessarily complex for most LLM applications. Instead of jumping straight to agent frameworks, developers should start with simpler workflow patterns like prompt chaining, parallelization, routing, orchestrator-worker, and evaluator-optimizer. These patterns solve most problems more reliably and are easier to debug. Agents work best in human-in-the-loop scenarios where oversight and flexibility are needed, but should be avoided for stable enterprise systems that require deterministic behavior.
Table of contents
Don't Start with AgentsWorkflow patterns you should useWhen to Use Agents (If You Really Have To)When NOT to use agentsTL;DRImagesSort: