Field notes, case studies, and the occasional opinion. Written by the people doing the work — researchers and ML engineers shipping production AI.
Everyone's building RAG systems these days, but most of them disappoint in production. After helping multiple teams get RAG right, here's what I've learned about the architectures, chunking strategies, and retrieval patterns that separate demos from real products.
AI agents are redefining enterprise operations by moving beyond simple automation into territory once reserved for human judgment — planning, reasoning, and acting autonomously across complex workflows.
Imagine a world where you could build sophisticated software that not only follows your instructions but also genuinely learns and adapts over time, all without you having to painstakingly pre-program every single rule and exception. That's not a futuristic fantasy; that's the tangible power of Large Language Models (LLMs), and it's fundamentally changing the landscape of software development — perhaps even rewriting the rules entirely.