The more I use AI (mostly DeepSeek), the more I realize a brutal truth: AI is just a mirror of the user's logic. If your thinking is all over the place, the AI will just give you fancy-sounding garbage. If you don't know how to verify what it spits out, you aren't building anything—you're just using a glorified, expensive search engine. I used to get burned all the time by code that looked perfect but completely broke in production. So I stopped trusting the "yes-man" behavior and forced myself to build a strict verification workflow. Here is what actually works for me: The "Devil's Advocate" Pass Never trust the first answer. Open a new chat and say: "Challenge this. What edge cases did I miss? Under what conditions would this break?" Anchor it to the Docs Stop asking "How do I do X?". Instead, feed it the official documentation and say: "Based ONLY on these docs, write the code. If you don't know, say 'I don't know'." Force a Confidence Score Ask it: "Rate your confidence in this answer from 1 to 10." If it's below a 7, I immediately go back to the docs. Without this framework, AI just makes you a faster producer of bad decisions. Side note: I got so sick of juggling different API keys and broken plugins that I built my own unified gateway (NieToken) to route text to DeepSeek and images to Doubao. I'm throwing in $0.5 in free credits for anyone who wants to test this workflow out. No strings attached. What does your verification process look like? How do you stop the model from confidently lying to you?   submitted by   /u/Nietoken [link]   [comments]