Category: AI & Data Science
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AI Model Distillation, Explained: The Compression Trick Behind the $589 Billion Monday
A single Chinese app knocked $589 billion off Nvidia in one day. The trick behind the panic has a boring name and a fascinating story.
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A 3-Point Gap and a 42x Price Cut: The Open-Weight AI Landscape, July 2026
The best open-weight model now trails the closed frontier by three points of measured intelligence and costs a third of the price. For anyone routing thousands of tasks through an API, that’s a procurement decision, not a nerd fight.
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GLM-5.2 and the Benchmark Trap: How One Score Becomes Two Headlines
A Chinese open-weight model just topped the leaderboards and undercut GPT-5.5 on price by 7x. Then the benchmark tables started disagreeing with each other.
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Designing Loops That Prompt Your Agents: The Shift From Prompts to Loops
A plain-English recap of Ray Amjad’s video on the prompts-to-loops shift: what a loop actually is, how inner and outer loops fit together, and how to keep them from drowning you in slop.
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Design for AI: What 40 Years of DFMA Teaches Us About Working With LLMs
Forty years ago, Boothroyd & Dewhurst showed that manufacturing cost was a design problem. Today, bad prompts and failing AI pilots are the same kind of mistake. Here are 7 principles for designing work that LLMs can actually execute.
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Anthropic Just Killed One of Its Own Prompting Tricks — Here’s What That Means
Six years ago prompting was a happy accident inside a GPT-3 paper. Today it’s the single skill separating AI winners from losers. Here’s the complete history — what Anthropic, OpenAI and Google actually published, and what still matters in 2026.
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Master Claude Code: A Free Interactive Training Program
Nine modules, quizzes, hands-on exercises, and a certificate — all in a single HTML file. A free training program to take you from Claude Code beginner to top 10% user.
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Prompting Just Split Into 4 Different Skills — Here’s How to Master Each One
Prompt engineering is dead. In its place, four distinct disciplines have emerged — Prompt Craft, Context Engineering, Intent Engineering, and Specification Engineering. This post breaks down the framework, shows where Klarna’s $40M AI bet went wrong, and gives you a concrete path to mastery.