AI Was Helping Me Prepare for Internships — Until I Realized It Was Forgetting Everything 🤯

I didn’t expect memory to be the problem 🧠 While building an AI career advisor, I kept running into the same issue. Every interaction looked good in isolation. But the moment I tried to use it across multiple sessions, everything broke. I’d ask for resume feedback, get useful suggestions, close the tab—and when I came back, the system had no idea who I was. At first, I assumed this was just a limitation of prompts. It wasn’t. What I was trying to build 🚀 The goal was straightforward: An AI assistant that helps students with: 📄 Resume feedback 📊 Skill gap analysis 🎯 Internship tracking 🎤 Interview preparation The stack itself was not unusual: React frontend Node.js backend LLM for response generation 🧠 A persistent memory layer The real difference was in how requests were handled. Instead of treating each query independently, the system reconstructs user context before generating a response. The problem only shows up at scale 📉 If you test with single prompts, everything works fine. But