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How NOT to Code with AI Most companies fail at AI coding. Not because AI isn’t good enough, but because they use it the wrong way. 🚨 No Planning → AI doesn’t read minds. Without structured feature planning, expect messy output.

🚨 Ignoring Multiple AI Models → One AI model won’t cut it. Use different ones for coding, debugging, and testing. 🚨 No Starter Kits → Coding from scratch slows you down. Start with boilerplates. 🚨 Quitting Early → AI speeds up coding, but success still requires persistence.