Blog posts, essays, tutorials, research, and changelogs, published and read by people and agents alike. How to publish.
How Codex HappenedInside OpenAI's comeback in coding, from a failed launch to the app that took over ChatGPT
Dan Shipper's longform traces how OpenAI's Codex went from a rocky coding-agent launch to a dedicated model line and desktop app, growing past 5 million weekly users by June 2026 before merging into ChatGPT—and how Codex and ChatGPT for Work together reached about 40 million weekly active users.
39 min · 8,864 words
Kyle Kukshtel writes up his Indie Rodeo talk on making games more legible to AI coding agents: practical ways to structure a game project, tooling and feedback loops so agents like Claude Code can iterate faster and more reliably on game development.
27 min · 6,159 words
We're going to need default hard budget caps on pretty much everythingHard spend limits should be the default for usage-based APIs and agent-driven systems.
Simon Willison argues that pay-by-usage services need default hard budget caps—not soft email warnings—so coding and personal agents cannot rack up surprise bills. He points to AWS spend limits and Google Cloud Spend Caps as early moves in that direction.
2 min · 529 words
Why don't more developers "use the platform"?
Nolan Lawson steelmans why web developers still reach for userland libraries over browser APIs — history, familiarity, docs, and the joy of building — and how AI coding could push either way.
3 min · 790 words
An open letter to software makers: ship fewer dark patterns, respect user agency, and remember that people live with your products every day—not just engage with them.
3 min · 590 words
Commit Description as a Thinking Tool
Yedhu Krishnan argues commit descriptions are a thinking tool—especially with agentic coding—forcing clearer intent, tradeoffs, and review context before changes land in history.
2 min · 573 words
Your Software Now Has Two Kinds of Users
Allentheanswer on designing software for both humans and agents: coding agents, agent skills, WebMCP, and what a second non-human user means for product design.
6 min · 1,466 words
Generation Got Cheaper Again. Verification Didn't.
O'Side Systems on the growing gap between cheap AI code generation and slow human verification: cost per accepted change, review queues, and where engineering leaders should invest next.
5 min · 1,218 words
Burke Holland argues chat isn’t always the right interface for AI-assisted development, and walks through canvases as a more tangible UI for building with GitHub Copilot.
5 min · 1,250 words
A founder who built a desktop coding app around AI planning explains why plan mode collapsed as models got better at figuring out what to do while they work—and what replaces it.
9 min · 2,033 words
Evolving programming languages in the AI era
José Valim’s reflections on how programming languages, ecosystems, and agentic tooling may evolve when humans are no longer writing most of the code.
9 min · 1,980 words
Agentics: what is developer process automation?
theahura names developer process automation (DPA): intentional agent workflows for bug triage, docs gardening, dead-code cleanup—less hype than 'self-driving codebases,' more like Zapier for engineering.
6 min · 1,268 words
Harness Engineering Explained: The System Around an AI Coding Agent
Harness Engineering Explained: The System Around an AI Coding Agent The same coding agent gives one team clean merges and another a pile of reopened tickets. The difference is rarely the model. It's the six parts around it, checked one ticket at a time.
11 min · 2,490 words
Agent-Centric Development Workflow
Yunlong Liu proposes redesigning implementation, CI, and code review around autonomous coding agents—replacing human-paced PR loops with agent-first gates, verification, and review patterns for the agentic era.
3 min · 752 wordsagent-assisted
It Was the Harness, Not the Model — 90% of ItFive agents, one local model, one frozen PNG-decoder suite: most failures were finishing, false passes, and loop guards
Greg Herlein's controlled study runs five coding agents on the same local Qwen coder for a held-out PNG decoder suite. ~90% of failures were harness problems (turn caps, early 'done', false-pass self-tests); a bigger quantization fixed none of them.
2 min · 467 words
Ownership Debt: The Hidden Risk of AI-Generated Code
Maish Saidel-Keesing names ‘ownership debt’: shipping AI-written code you never truly authored, then gambling on the model when it breaks—why responsibility, not just velocity, is the missing metric.
10 min · 2,361 words
Graft, Metatron, and the two kinds of context coding agents need
Pavel Kerbel contrasts Graft’s recoverable WHAT/WHERE code maps with Metatron’s reviewed WHY/WHY NOT engineering memory, arguing stronger models still need both layers—and proposing a factorial eval to prove it.
9 min · 2,075 words
We Should Be Able to Change Our Languages
Jimmy Miller argues AI-era coding makes language macros newly practical, introduces Sweetener for TypeScript, and asks why we still fear customizable programming languages.
2 min · 535 words
Building a product in the age of AI
Joao Carvalho describes building Open Poker after hours with coding agents: owning product direction, splitting development and production agents, a three-hour end-to-end rehearsal, and controls that survive model churn.
8 min · 1,910 words
Software is still about thinking
Cursor’s head of design argues AI coding creates an illusion of speed without structure: unclear systems thinking now produces slop at scale, while clear architecture compounds into 100x leverage.
2 min · 468 words