Step-by-Step Tutorial
Blogs written in the “Step-by-Step Tutorial” format.
Hallucination Debugging: Concrete Techniques for Trustworthier Model Output
A model stating something false with total confidence isn't a bug you can patch out - it's a pattern you have to design around. Here are the practical techniques that actually move the needle on hallucination risk.
Getting an LLM to Output JSON You Can Actually Trust
Tell a model to 'return JSON' and what you often get back is JSON-shaped, not JSON-valid. Here's a practical look at what actually gets you reliable, parseable structured output from an LLM.
What Real ROI on an AI Tool Actually Looks Like Before You Sign
Feeling more efficient isn't the same thing as proving it. A concrete way to test whether an AI tool earns its cost, both before you buy it and after you're running it.
Put AI to Work on Your Weekly Report: A Practical Walkthrough
A practical, step-by-step guide to getting AI to turn your scattered notes and raw numbers into a workable first draft of your weekly report - including the exact spots where you still need to check its work.
Your First LLM API Call, Explained Piece by Piece
What actually happens under the hood the first time you hit an LLM API - the request body, the response you get back, and the slip-ups beginners run into again and again.
A Simple Day-by-Day Blueprint for Working With AI
This isn't a scattered list of tips - it's a complete, realistic daily workflow that shows exactly where AI fits in, from planning your morning to wrapping up at night.