Developer shares practical blueprint for building reliable AI agents in production

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A developer at HookLabs AI has published a candid guide on DEV Community outlining what it actually takes to ship production-grade AI agents. The article pushes back against overhyped 'no-code in two hours' claims, noting that real-world agent builds routinely face crashing webhooks, context window overflows, and hallucination loops. The author recommends three core safeguards: sanitizing all user input before it reaches the language model, setting maximum iteration limits to prevent runaway agent loops, and preparing fallback responses for when the AI fails. The piece argues that tweaking prompts alone does not constitute genuine engineering, and that developers must understand the underlying mechanics of AI systems to avoid gambling with production code.

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