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7 Practical Tips to Make AI-Generated Code More Reliable and Ship-Ready

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A developer has distilled months of experience building with AI coding tools into seven actionable tips for improving the predictability of AI-generated code. The advice stems from a talk titled 'It's Dangerous to Code Alone! Take This: Developer's AI Survival Guide,' which prompted repeated requests for a written version. An MIT study of over 100,000 developers found that while AI agents increased code written by roughly 180%, code that actually reached production grew by only about 30%, highlighting a significant reliability gap. To illustrate the tips, the author built a link-sharing platform using tools like Codex GPT and Figma MCP, with an AWS Blocks backend replacing local mocks. Key recommendations include writing clear, unambiguous prompts, providing input-output examples, and instructing the model to reason step by step before generating code.

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