Practical takes on AI, product thinking, and rapid prototyping. Written by builders, for builders.
Cutting through the noise: what vibe coding actually is, how long it takes to learn, whether it's worth your time, and where to start if you're serious about building with AI.
Too many tools. Too many approaches. Too many 'best practices.' Here's why data analytics beginners get stuck before they even open a dataset, and the simple mindset shift that fixes it.
You've cleaned the data, made visualizations, found patterns. But it still doesn't feel complete. Here's why data analytics students struggle to ship, and how to know when analysis is actually finished.
The shift from reactive chatbots to autonomous agents isn't just about better prompts. It's about giving AI the ability to plan, act, and learn from results.
Giving an AI access to tools sounds simple until you hit real-world edge cases. Here's what we've learned building dozens of agents in production.
The gap between 'it works on my laptop' and 'it runs reliably for users' is filled with details nobody talks about in tutorials. Here's the real deployment checklist.
Forget the hype. Here's a step-by-step approach to building an agent that actually solves a problem you have today, not a theoretical one you might face tomorrow.
You've completed 47 tutorials and still can't build your own agent from scratch. The problem isn't your intelligence or effort—it's that tutorials teach answers, not questions.
The docs tell you how. But they don't tell you when, why, or if. That's the gap where most AI projects die. Here's what fills it.
Most people learn AI in scattered evenings over months. A tiny fraction ships working products in a single day. Here's why compression creates clarity that duration never will.
You've watched the tutorials, read the docs, even built a few examples. But something's missing. Here's why self-directed learning stalls, and what actually gets you unstuck.