What I Learned Building an AI Tutor: RAG, Prompt Design, and Its Limits

<p>You opened ChatGPT before Slack this morning.<br /><br /> Not for anything complicated. Just to figure out how to begin.</p> <p>That small move is already changing what

<p>Imagine you have a super-smart assistant. This assistant can write stories, create images, or even help plan your day. All you have to do is tell it what you want. You don't

<h2> The Problem Nobody Talks About </h2> <p>You've built an agent. You've wired up 100+ tools. You feel good about it.</p> <p>Then it starts hallucinating. Picking the wrong

<h1> RAG Systems in Production: Building Enterprise Knowledge Search </h1> <h2> Introduction </h2> <p>Retrieval-Augmented Generation (RAG) has revolutionized how enterprises build

<p>Most developers who build AI agents make the same mistake: they spend weeks designing the orchestration layer, tuning the system prompt, and picking the right model — then hand

<!-- SC_OFF --><div class="md"><p>We spent the last year building a code indexing system and tried pretty much every retrieval approach along the way. Sharing what actually worked

<h2> From Overwhelm to Insight: Navigating the Modern Code Jungle </h2> <p>You clone a promising repository, ready to contribute or understand its magic. You’re greeted by dozens

<p>For the last few years, building with large language models often started with one question:</p> <p><strong>“What prompt should I give the model?”</strong></p> <p>Developers