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  How I’m Teaching My AI Agent to Learn From Its Own Mistakes — Without Any Retraining How I’m Teaching My AI Agent to Learn From Its Own Mistakes — Without Any Retraining 📌 Introduction: I’m Not an AI Expert, Just a Builder Hey there 👋 I’m Ashutosh, 18 years old, currently in my 2nd year of BSc Computer Science. But honestly, most of what I know about AI didn’t come from textbooks — it came from building tools, breaking things, and fixing them. Today, I want to share something powerful I’ve been working on: Teaching my AI agent to learn from its own mistakes . No retraining. No fine-tuning. Just smart logic and iteration. If you’re building with GPT, LangChain, or CrewAI — this blog will help you go beyond basic prompt chains. 😬 The Problem: My Agent Was Repeating Mistakes I built a Resume Evaluator agent inside my projec. Upload a resume → get feedback. But it wasn’t always working well. Either the advice was too generic, or it missed obvious mistakes. And worst...

“How I’m Making My AI Agent Smarter Than Prompt Chains — From Debugging to Deployment” 👋 Intro: From Prompt Follower to Real Thinker Let me be honest — I’m still learning. I’m a 2nd-year BSc CS student trying to build production-level LLM tools. But this past month, I realized something dangerous: Most AI agents are just smart parrots. They don’t remember, adapt, or think. And if you don’t design better logic, they never will. That’s when I made a decision: I won’t build just another chatbot . I’ll build autonomous AI agents that actually get smarter with time. Here’s how I’m upgrading my agents — even as I learn and debug daily. 🔧 Problem: Agents Are Dumb (By Default) At first, I built my agent using simple tools: LangChain chains Prompt templates Basic task routing But every time I gave it a complex task — like evaluating a resume or suggesting a career path — the agent would: Forget what I said earlier Repeat generic answers Hallucinate fac...