TL;DR I tracked 6 months of my own AI coding sessions in React Native. In my logs, 42% of AI-generated diffs contained at least one hallucinated import, fake API, or duplicate component. Token costs were the second tax. Re-loading project context every session cost roughly $135/month per developer at the model pricing I was using. Better prompts didn’t fix either problem. The AI didn’t need smarter instructions : it needed memory and a map. I built U-AMOS (Universal AI Memory Operating System): a 3-tier memory bank, a context map, a rule priority system that splits “what to do” from “how to do it,” a 7-point anti-hallucination checklist, and a plan/act workflow that runs before any code is generated. After deploying U-AMOS across my own projects over a 3-month tracking period: hallucinations dropped from 42% to 3%. Token costs dropped from $180/month to $18/month. Feature velocity increased roughly 5x. These are my internal numbers: I’ll note where external research reports similar magnitudes.…