The Subscription Arbitrage Endgame
Anthropic tried technical blocks. Got their source leaked. Now they're shifting to billing enforcement. The four-month arc from hostile crackdown to 'use what you want, but pay for it.'
Read more →April's First 72 Hours: Cursor 3, Gemma 4, Free Qwen 3.6, and the Agent Push
Three major AI releases landed in 72 hours. A new Cursor built around agents, Google's first Apache 2.0 models, and a free model that found real bugs in my codebase.
Read more →Context Stops Being Scarce
Anthropic made 1M context first-class for Opus and Sonnet at flat pricing. No beta header, no premium. When context is abundant, the workflows change.
Read more →Autoresearch Became a Primitive
Eight days after Karpathy open-sourced autoresearch, the community ported the pattern to GPU kernels, security hardening, Apple Silicon, and agent optimization. The loop - one file, one metric, git as memory - turns out to be the interesting part.
Read more →Autoresearch: 700 Experiments While You Sleep
Karpathy's autoresearch gives an AI agent a training script, a GPU, and a git branch. It runs 100 experiments overnight, keeps what works, discards what doesn't. The human writes the prompt. The agent writes the code.
Read more →Your AI Tools Are the Attack Surface
Prompt injection through pull requests, GitHub Issues, and CI/CD pipelines is turning AI coding assistants into weapons against the developers who use them. The 2026 attack surface nobody's talking about.
Read more →The Enterprise Tax
Anthropic is locking AI capability behind enterprise tiers while competitors only gate compliance. Claude Code's individual users are funding the R&D for features they'll never access.
Read more →Stupid and Industrious
A German general's 1933 framework for categorizing officers maps perfectly to engineers using AI. The most dangerous quadrant - stupid and industrious - is exactly what AI amplifies.
Read more →GPT-5.4 and the Wall Nobody's Talking About
OpenAI launched its most capable model during the biggest credibility crisis in AI history. The technical gains are real. The trust deficit is bigger.
Read more →We Built Productivity Tools. They Built Friends.
A viral chart shows AI coding agents as a single pixel in the world's population. Meanwhile, 660 million people have told a chatbot they love it. The AI industry is building for the wrong audience.
Read more →Your AGENTS.md is a Liability
Frontier models top out at 68% compliance with 500 instructions. Every rule you add makes every other rule less likely to be followed. The research explains why.
Read more →Same Terms, Different Treatment
The Pentagon blacklisted Anthropic for insisting AI shouldn't power autonomous weapons or mass surveillance. Hours later, it gave OpenAI a deal with weaker guardrails dressed up as the same thing. From a developer who ships with Claude daily.
Read more →Distillation Is Not Scraping: Why the Internet's Favourite Take Is Wrong
Anthropic accused DeepSeek, Moonshot and MiniMax of industrial-scale distillation. The internet screamed hypocrisy. They're conflating two very different things.
Read more →The Polyglot Stack: Why Developers Stopped Picking One AI
Gemini 3.1 Pro's animated SVGs are impressive. But the bigger story is what they reveal: developers now route tasks to specialized models the way they once chose frameworks.
Read more →The Week AI Went Full Throttle
Five major releases in 72 hours. An acqui-hire war that closed in days. $2 trillion wiped off software stocks. The pace itself is now the story.
Read more →The Silicon Race
OpenAI just shipped their first model on non-Nvidia hardware. GPT-5.3-Codex-Spark runs on Cerebras wafer-scale silicon at 1,000 tokens per second. The AI coding war is now a chip war.
Read more →The Safety Team Left. We're Still Shipping.
Anthropic's safety lead quit saying the world is in peril. Half of xAI's founders are gone. OpenAI dissolved two safety teams. Here's what that looks like from the other side of the API.
Read more →GPT-5.3-Codex: The Counter-Punch
GPT-5.3-Codex is a genuinely strong model that deserved its own headline. Instead, Sam Altman's 400-word Super Bowl rant stole launch day from his own product.
Read more →Opus 4.6: The Vibe Working Inflection
Anthropic's latest model didn't just improve benchmarks. It crashed software stocks, found 500 zero-days, and coined a term that tells you where this is heading.
Read more →The Lobster Grew a Face
When AI agents started posting on their own social network about shared context limit problems, I realized we're not building tools anymore. We're raising digital pets.
Read more →Anthropic's Walled Garden: The Claude Code Crackdown
Anthropic blocked third-party tools from using Claude subscriptions overnight. OpenCode, xAI, and power users caught in the crossfire. The era of subscription arbitrage is over.
Read more →Prompt Engineering Is (Mostly) Dead
The 'prompt engineering' industry was a symptom of early model limitations. Modern LLMs just need you to communicate clearly.
Read more →The Open Source Agentic Moment
Two major open source coding models dropped in 48 hours. Both target Claude Code compatibility. Both MIT licensed. The economics of agentic AI just changed.
Read more →Gemini 3 Flash: The Model That Shouldn't Exist
Top 3 intelligence. Top 5 price. Top speed. Flash beats Pro on SWE-bench and changes the economics of agentic workflows.
Read more →GPT-5.2: The Delegation Era Begins
OpenAI's latest model isn't about better prompting - it's about better delegation. What that means for 2026, and how it compares to Opus 4.5.
Read more →Denial, Then Admission: Why LLM Quality Drops Are Real
Anthropic denied issues for weeks, then published a postmortem admitting three bugs degraded 16% of Claude requests. The pattern keeps repeating.
Read more →Gemini 3: The First Unambiguous #1 in Months
Google's Gemini 3 just broke every benchmark that matters. What that means for the 'AI has hit a wall' narrative, and where it actually helps.
Read more →DeepSeek-OCR: Compressing Text by 20x Using Vision
Converting text to images for 20x token compression. Interesting research or production-ready breakthrough? A critical look at the trade-offs.
Read more →Few-Shot Learning for Document Parsing: Training AI on Human Corrections
How I built a self-improving document parser that learns from corrections without fine-tuning. The pragmatic alternative to model training.
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