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Your prompts are fine. Your AI output is still garbage. You write carefully. You're specific. You ask for the format, the tone, the length. Hit enter. The AI responds with something that sounds like it was written by a committee of lawyers having a really bad day. Here's what you don't realize: You're not telling the AI to do something. You're describing the problem, and the AI is solving for the statistical average. The fix isn't more detailed instructions. It's three examples. That's it. Three. Not ten, not one, three. This post is the complete guide to few-shot prompting — the single highest-leverage move in prompt engineering. By the end, you'll have a template you can copy into any AI and watch your output quality jump 5x. Prefer watching? Here's the 3-minute version Otherwise, read on — everything's below. Why Instructions Fail (And Examples Work) When you tell an AI to "be funny," it's working off a fuzzy statistical average of everything labeled "funny" in its training data. When you show an AI what you think is funny, you're giving it a precise pattern to match. Here's the difference: ❌ Instruction: "Write a funny one-sentence movie summary" Result: A lukewarm joke that lands in the middle of the comedy bell curve. ✅ Pattern: Funny summary of The Lion King: Cub loses dad. Cub becomes king. Funny summary of Finding Nemo: Dad fish swims very far for his son. Funny summary of Titanic: [AI fills this in] Result: Boy meets girl. Boat meets iceberg. Oops. Same AI. Different universe. The only thing that changed: you showed it the pattern instead of describing it. The Science (Why This Isn't Magic) Language models predict the next token by pattern matching. They've seen millions of prompt-response pairs and learned: "When a prompt looks like this , the output usually looks like that ." One example could be a fluke. Two examples might be a coincidence. Three examples are clearly a pattern. The AI recognizes the pattern and completes it. This is exactly how humans l

Hello, I wanted to share with you all a interactive map of the economics and physics constraints of the AI buildout. It has macro drivers, industrial chokepoints, and where that shows up in markets. I've added 393 nodes and 562 edges to capture other supply / physics constraints as well. There's no sign up, and no pay wall, it's all free. Please let me know what you think!

HaloBraid aims to help salons speed up braiding with its first device, slated to launch later this year, that acts as a braiding assistant for professional stylists.

Hey HN. http://peerd.ai is an AI agent harness that lives entirely in your browser as a web extension. You don’t have to install a separate “AI browser”. You don’t have to bolt on or run some external process or manage a clunky mcp integration. It’s just a fully contained web extension, written in no build vanilla JS with minimal non-browser dependencies, using your own provider keys, and Apache 2. This isn’t just a fun hack. While it has largely been a solo side project, I genuinely believe the

Hi all! TikZ is a widely-used LaTeX package for drawing figures in papers. It uses commands like \draw[->] (0,0) -- (1,2); to draw lines, shapes, text, etc. Academics usually code up their figures by hand, so there is lots of twiddling around with the coordinates and recompiling until things look nice. I guess it’s a bit like SVG, but it’s more code than markup, for example it has loops with \foreach. I built an open-source WYSIWYG TikZ editor (available for web and desktop) that allows you to e

The smart glasses are available in several countries starting today in a variety of color and lens combinations.