Don't use an agent where a sequence works: the biggest AI-building mistake, per Hugo Bowne
hugobowne · x · 2026-09-17
Hugo Bowne-Anderson argues one of the biggest mistakes in building with AI is deploying an agent where a perfectly good fixed sequence exists.
- Sales call example: transcribe, extract fields, have the salesperson verify, update CRM — keep the sequence in code and use LLMs inside it; letting the model decide what's next adds decisions to test and debug.
- An agent earns its place only when the next step depends on what it discovers, like a coding agent inspecting a failed test and deciding what to change.
He's teaching a free Lightning Lesson, "Five Mistakes Everyone Makes When Building AI Agents," also covering frameworks that hide what you need to debug, adding features instead of fixing failures, and giving the model control over decisions that belong in code.
Related event: Expert Warns Against Overusing Agents in Fixed Workflows(3 posts)→
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