When a developer gives an AI agent a coding task, the agent does more than answer once. It plans, generates code, runs tests, and repeats the process to correct errors. A single task can use 10 to 50 times more tokens than a basic chat prompt.
How I Built the Most AI-Pilled Company in the World Don't be put off by the clickbait headline, this piece by Jacob Sansbury describing how they are building Spawn is a fascinating exploration of the bleeding edge of what's possible with agentic engineering against frontier models.
Anthropic manager Felix Rieseberg says the classic coding interview is dead because Claude now solves small programming tasks better than job candidates do. He'd rather see prototypes that show taste, empathy, and principled thinking, since in his words, "hunger beats tenure."
I've written before about how November 2025 was an inflection point for coding agents - the point where Opus 4.5 and GPT-5.1 crossed a tipping point that meant their respective coding agents became reliable daily drivers for software engineers. I think we've reached a new inflection point in October 2026, and this time it's for vibe coding computer games .
Retro video games are everywhere lately - especially in places where they aren't supposed to be. Halo in a web browser, Wind Waker on the iPhone, Super Smash Bros. in mixed reality.
Paying for outcomes, building with agents, and the last mile of enterprise AI adoption
My obituary for programming Jeremy Scheff poignantly captures the key loss caused by coding agents for career programmers who enjoyed the puzzle of developing code: Programming turned into one of the greatest jobs you could imagine. You got paid to work on tricky little logic puzzles. The trickier the puzzle, the more you got paid.
Addy Osmani, Morgan Westlee Lunt and Qing Wang describe how the Claude Code team does code review: instead of treating "did a human read the code?" as the test, they ask "what could go wrong with this change, and which check should catch it". Review has thus moved from a gate at the end of a PR to something continuous, with most changes reviewed and fixed by Claude at least once before a human looks.
Replit CEO Amjad Masad envisions a future of “self-driving companies,” where AI agents handle day-to-day tasks and people focus on higher-level decisions.
Geoffrey Huntley proposes using a pre-commit hook to inspect the git diff, reject commits that call observability modules directly and bypass the diagnostics module, and inject a prompt telling the AI agent to use the diagnostics library instead. He argues that updating AGENTS.md alone still leaves a delta and will drift, whereas this approach made the agent's performance instantly ten out of ten.
Andrej Karpathy, co-founder of OpenAI and now at Anthropic, sees a widening knowledge gap in AI. About 75 percent of the world's population has barely touched LLMs. Roughly 5,000 people, meanwhile, have access to internal frontier systems whose agent swarms do work that would take top experts years. The public, at best, sees a weird chatbot.
Shipping Opus/Sonnet 5.5, Mods, Plugins, Projects, Tag while Pacing the Frontier
On Friday I gave the closing keynote at the WeAreDevelopers World Congress North America in San Jose. I tied together the key trends from the past year into a chronological exploration of everything that happened in 2026. The video is on YouTube ; here are my annotated slides and notes to accompany the talk.
The more time I spend working with coding agents, the more convinced I am that they make software engineering even harder. We can do amazing things with them, but unlocking their full potential requires extraordinary discipline and knowledge.
An engineer half a month into a new role at a big company says the team's specs, code, tests, PRDs, tickets and their resolution, reports and more are all generated by Claude Code. Nobody on the team likes it, but they are being forced to ship as much as they can. He says he has heard multiple times from higher management that pushing code is not a bottleneck, and that people work 12 to 13 hours a day just to press enter, with everyone from L1 to L7 engineers doing the same thing and nobody reading anything.
We dive into these questions and other AI hot takes on the latest episode of the GitHub Podcast.
The first step towards recursive self improvement