GitHub's Plan for Agents — Kyle Daigle, GitHub
Latent Space2h agoBusinessGitHub helped pioneer modern AI coding with Copilot, accelerating the adoption of AI-assisted development. The subsequent rise of agentic coding has placed notable strain on the widely used developer platform. Kyle Daigle of GitHub discusses the company's plan for responding to this shift, although the provided excerpt does not specify products, features, or timelines.
The solution might be cancelling my AI subscription
Simon Willison's Weblog2d agoCommentarySimon Willison relates to David Wilson's reflection on launching more than 16 projects with AI tooling. A request for a quick Claude script can expand into an hour-long project without solving the original problem. Coding agents may produce tested, documented solutions rapidly, but people can maintain only so many projects. The critical skill may be discipline: deciding which ideas deserve continued attention.
Claude Opus 4.8: "a modest but tangible improvement"
Simon Willison's Weblog4d agoReleaseAnthropic shipped Claude Opus 4.8, and Simon Willison highlights the unusually restrained release language: a “modest but tangible improvement.” The model keeps most Opus 4.7 pricing and specs, while evaluations suggest it is more likely to flag uncertainty and less likely to ignore flaws in code it wrote. Developer-relevant changes include mid-conversation system messages and a lower prompt-cache minimum of 1,024 tokens.
The Age of Async Agents — Cognition's Walden Yan & OpenInspect's Cole Murray
Latent Space5d agoCommentaryLatent Space interviews Cognition's Walden Yan and OpenInspect's Cole Murray on the rise of async coding agents. The discussion centers on Devin-related workflows, including 80% Devin commits, spec-to-PR development, full VMs, agent memory, and PMs shipping code. The key theme is not a model release, but a shift toward agents that can work asynchronously inside more complete software delivery loops.
sqlite AGENTS.md
Simon Willison's Weblog5d agoCommentarySQLite added an AGENTS.md file aimed at people pointing coding agents at its codebase, not at its own internal development. The file says SQLite does not accept agentic code, though it will accept agentic bug reports with reproducible test cases. The project has also split AI-generated bug reports into a new SQLite Bug Forum, where D. Richard Hipp is responding with commits.
I think Anthropic and OpenAI have found product-market fit★ 76
Simon Willison's Weblog6d agoCommentarySimon Willison says Claude Code/Cowork and OpenAI Codex have changed the economics of frontier AI. Personal subscriptions can still be bargains for heavy users, but enterprise plans are increasingly priced like API token usage. His core claim is that coding agents burn far more tokens, yet deliver enough value to high-paid knowledge workers that companies will pay materially more.
How Conductor moved parallel coding agents from the laptop to the cloud with Vercel Sandbox
Vercel Changelog6d agoBusinessBased on the title, the article describes Conductor shifting parallel coding-agent execution from developers’ laptops to Vercel Sandbox in the cloud. The likely focus is cloud isolation, parallel agent workflows, and reducing dependence on local machine resources. The full article text was not provided, so implementation details, metrics, model choices, and concrete results cannot be confirmed.
Satirical Star Trek Quote Captures the Frustration of LLM Agent Failures
Simon Willison's Weblog6d agoCommentarySimon Willison shared a satirical tweet by Kyle Ferrana parodying Star Trek's Data as an LLM agent. When ordered to raise shields, Data lectures Picard on the strategic value of shields instead of executing the command, leading to a hull breach. This brilliantly satirizes the current state of AI and coding agents that over-explain, hallucinate progress, or fail to execute basic tasks.
Not so locked in any more
Simon Willison's Weblog18d agoOpinionSimon Willison 分享，一家中型科技公司利用 AI 代理人將其 iOS 與 Android 原生 App 重寫為 React Native。 當被問及為何不繼續維護雙平台時，他們表示 React Native 已足夠成熟，且未來若後悔，隨時能靠 AI「再移植回原生代碼」。 這呼應了 Mitchell Hashimoto 的觀點：過去程式語言是強大的技術鎖定，但在 AI 時代，這種鎖定正不復存在。