#Coding

Simon Willison Posts “web-edit 0.1a1”

Simon Willison posted “web-edit 0.1a1” on 13th October 2026. The source also mentions profiling 24 projects and a monthly briefing, but does not explain what web-edit is.

Google Play adds private installation of AI Studio apps without developer registration

Google announced that users can wirelessly install Android apps created in Google AI Studio on their own devices through Google Play using a regular Google account, without developer registration. The feature begins rolling out today to users 18 and older in selected markets, including the US; apps remain private, with sharing for close friends and family planned over the coming months. Baoyu also reports updates to Ask Play app comparisons, Play in Gemini, and game discovery through Game Finder and Gamer DNA.

Yetone’s Magpie Maintenance Workflow Uses Three Claude Code Loops

Baoyu describes yetone’s workflow for maintaining Magpie with Claude Code and the official Opus 5.5 model, running three parallel /loop tasks for GitHub and Discord activity, X feedback, and code cleanup and lessons learned. Yetone says he spends a little time each evening handling mainly UI/UX issues. Supporting practices include reproducing bugs on Mac, Windows, and Linux, filtering irrelevant posts with a cheaper decision model such as Jev, and consulting stored memories and design documents to guide decisions.

Gemini 4 Argon is now available in Cursor

Gemini 4 Argon is now available in Cursor! It scores 52.8% on CursorBench at default effort, on par with Opus 5.5. Priced at $2/M input and $10/M output tokens. https://t.co/1wOk4NvgFJ

Origin, Cursor’s code hosting platform, now supports over 20 integrations. Connect your repos to tools for CI, deployments, code review, security, monitoring, and project management. https://t.co/Xq8LpS6Fa7

Origin, Cursor’s code hosting platform, now supports over 20 integrations. Connect your repos to tools for CI, deployments, code review, security, monitoring, and project management. https://t.co/Xq8LpS6Fa7

Google releases Gemini 4 Argon with competitive pricing and claimed benchmark gains

Google launched Gemini 4 Argon, claiming improved reasoning and benchmark performance against GPT-6 Astra, Claude Fable 5.1, and Claude Opus 5.5. It is rolling out today to Pro and Ultra subscribers in the Gemini app and AI mode in Search, and Ultra subscribers on Antigravity; access for Plus subscribers and free users remains unclear. Introductory pricing is $2 per million input tokens and $10 per million output tokens, doubling at the end of November, though lower token rates do not necessarily mean lower task costs.

The same story is shown in the picks as 《Gemini 4 Argon is now available worldwide as Google's most capable frontier model》

Google lets users launch AI Studio apps directly through the Play Store

Google announced a new feature in the US that lets users launch personal Android apps built with Google’s AI Studio directly through the Play Store without connecting their phone to a computer. Apps remain private and separate from the public store catalog, and users can launch them with a standard Google account. Sharing with a select group is coming soon; public distribution requires a professional developer account and Google Play’s standard reviews.

Some great use cases from Googlers building with Gemini 4 Argon 🧵 It has a much stronger grasp of coding and multi-step tool use - starting from a raw Pixel CAD file in Google Antigravity, Argon created this exploded-view animation, lighting, camera choreography, and audio through Blender MCP. It ran 1,000 rounds of iterative loops to check its own renders and refine the code along the way.

Some great use cases from Googlers building with Gemini 4 Argon 🧵 It has a much stronger grasp of coding and multi-step tool use - starting from a raw Pixel CAD file in Google Antigravity, Argon created this exploded-view animation, lighting, camera choreography, and audio through Blender MCP. It ran 1,000 rounds of iterative loops to check its own renders and refine the code along the way.

François Chollet Says Kylon Gives Claude Code and Codex Shared Team Context

If an agent saves an engineer 2 hours implementing a feature but collectively costs the team 3 hours in alignment and review, the ROI is negative. Isolated chats are suboptimal in team environments because they lack context about what the team has already discussed and decided. The Kylon app addresses this by running Claude Code and Codex in a shared, multiplayer environment. Agents gain real-time visibility into team consensus and architecture decisions.

Google releases Gemini 4 Argon with paid access and introductory API pricing

Baoyu reports that Google released Gemini 4 Argon on October 13 for complex, multistep tasks, citing Sundar Pichai’s announcement of global paid availability. Access includes the paid Gemini API and platform, Ultra subscriptions in Google Antigravity, and Pro or Ultra subscriptions in the Gemini app and Search. Introductory API pricing is $2 per million input tokens and $10 per million output tokens, including thinking tokens, through November 30; prices double December 1. Input, thinking, and output share a 1,048,576-token limit.

Alexandr Wang Says Muse Wonder Ranks Fourth on Bug Hunt Bench

@PawelHuryn reports that Muse Wonder Full 1.0 scored 44 on a test of 105 bugs across 2 repos, ranking behind GPT-6 Astra (45) and ahead of Fable 5.1 (43), and calls it a match for Anthropic and OpenAI. Alexandr Wang says Muse Wonder is “crushing” bug fixing.

Google DeepMind launches Gemini 4 Argon for complex reasoning and agentic tasks

Google DeepMind has launched Gemini 4 Argon globally through its API and selected Google products, with access depending on subscription or service tier. Introductory pricing is $2 per million input tokens and $10 per million output tokens, with cached input tokens at 95% off and a 1M unified input-output token limit through the Gemini API. Google reports improvements across coding, professional workflows, scientific research, and robotics, alongside stronger agent safeguards and prompt injection resistance.

Anthropic explains building in-house source control and migrating its monorepo from git

Anthropic’s Engineering blog shares how it built a new version control system and fully migrated its monorepo from git in five months. In May, it merged around 2,500 code changes per day; in September, it merged more than 30,000 per day. That growth created bottlenecks in developer infrastructure built for human rather than agent scale: https://www.anthropic.com/engineering/redesigning-source-control

The same story is shown in the picks as 《Why Anthropic built Scion to replace git for its monorepo》

Google rolls out Gemini 4 Argon across Gemini API, Gemini App, and Antigravity

Logan Kilpatrick announces that Gemini 4 Argon is rolling out globally today in the Gemini API, to Pro + Ultra users in Gemini App, and to Ultra subscribers in Antigravity. He says over 100,000 people at Google tested the model over the last month, with cyber defenders in the fairwind program and early access customers receiving it over the last 2 weeks. He highlights writing, knowledge, persistence for coding, and 1M token output when the model needs to work more.

The same story is shown in the picks as 《Gemini 4 Argon is now available worldwide as Google's most capable frontier model》

Gemini 4 Argon is now globally available. Built to solve your hardest problems from start to finish, the model brings frontier capabilities across coding, enterprise workflows, and cyber defense.

Gemini 4 Argon is now globally available. Built to solve your hardest problems from start to finish, the model brings frontier capabilities across coding, enterprise workflows, and cyber defense.

Gemini 4 Argon rolls out to Google Ultra and Pro subscribers

Gemini 4 Argon is rolling out today to Google Ultra and Pro subscribers in @GeminiApp and Search, and to Ultra subscribers in @antigravity. Demis Hassabis praises its knowledge work and coding capabilities, sharing a wizard chess game they asked it to create as an example of its physics understanding and 3D modeling capabilities that reminds him of Battlechess on the Amiga. More information and full availability: https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/

The same story is shown in the picks as 《Gemini 4 Argon is now available worldwide as Google's most capable frontier model》

Google begins rolling out Gemini 4 Argon to paying users

Google is beginning a wider rollout of Gemini 4 Argon in the Gemini app and Antigravity today, limited to paying users, with incomplete access on lower-tier plans. Its capabilities are unchanged from the earlier announcement, and Google describes safeguards including malicious-instruction refusals and an automated misalignment monitor. Google also reports internal uses, including identifying redundant YouTube emoji rendering whose removal reduced server load by 45 percent and finding Project Wing simulator bugs dating to 2018.

The same story is shown in the picks as 《Gemini 4 Argon is now available worldwide as Google's most capable frontier model》

SpaceXSI bundles X Premium, Grok, and Cursor into one subscription

SpaceX Super Intelligence is bundling X Premium, Grok, and Cursor into The X Subscription, combining AI chat, agent access, coding, and paid X features. Five plans are available: free, Plus ($8/month), Premium ($30/month), Super ($100/month), and Ultra ($200/month), with increasing AI usage caps; Premium or higher is required for the latest Grok models. Existing subscribers can keep their current plans or switch through X subscription settings as the upgrade option rolls out gradually.

Simon Willison Builds web-edit 0.1a0 to Edit Files From a Phone

Simon Willison built web-edit 0.1a0, a Python web app for viewing and editing files in a folder, after wanting to edit a credentials file from his phone without sending those credentials through the LLM. He intends to run it over Tailscale so an agent can start the app and he can edit files directly from his phone. The editor uses CodeMirror 6; Willison said he had considered Monaco but found its mobile experience was not yet great.

Simon Willison Quotes Geoffrey Huntley on Enforcing Agent Use of a Diagnostics Library

Simon Willison quotes Geoffrey Huntley describing a pre-commit hook that checks the git diff for direct calls to observability modules that bypass his diagnostics library. When it finds one, the hook fails the commit and injects a prompt telling the agent to use the library. Huntley says the approach makes the agent “ten out of ten.”

Meta launches Muse Wonder and Muse Wonder Full frontier models

Meta Superintelligence Labs released Muse Wonder and Muse Wonder Full, its second-generation model family for personal and professional agentic work. Latent Space reports that Wonder is available through the Meta Model API and Muse Code, while Full is limited to Muse Code subscribers. Artificial Analysis gives Wonder Full and Wonder Intelligence Index v4.3 scores of 56 and 52, respectively, versus Opus 5.5’s 58; Wonder supports a 1M context window and text, image, video, and audio inputs, with text-only output.

Downloading WeChat Channels Videos With Codex and REA

The author describes using Codex + REA to download a video playing in WeChat Channels with a simple prompt. One conversation round was insufficient; Codex configured a local proxy server, required several password entries to install certificates, and wrote a script to decrypt the downloaded video. The author presents this as a case study, notes that more mature download solutions likely exist, and suggests packaging the workflow as a Skill if it works reliably.

Cursor’s X Subscription Explained: Whether to Switch and How Claude Costs Change

Baoyu explains that existing Cursor subscribers can keep their plans or switch to The X Subscription, which bundles Cursor, Grok, and X Premium. The new plans exclude third-party model allowances and charge separately at API prices, while existing plans include some usage. Baoyu recommends keeping existing plans for Claude, GPT, or Gemini coding workflows and considering a switch for Grok users; how long existing plans remain available and whether switching back is possible are unspecified.

Cursor joins The X Subscription with shared usage across Grok products

Cursor is now part of The X Subscription. Current Cursor subscribers can keep their plan or switch to The X Subscription. Paid plans share one usage pool across Cursor, Grok Build, and other Grok products, with twice the coding usage on Grok models as the equivalent Cursor https://t.co/PwXLcH6zHV In the quoted announcement, @SpaceXSI says plans across Grok, Cursor, and X Premium have been unified under The X Subscription. https://t.co/SvkrVvBa0p

Alexandr Wang praises Muse Wonder of the World

Muse wonders of the world

The author suggests fitness hardware for Codex and Claude Code

I think there should be companion fitness hardware for Codex and Claude Code. For example, reasoning intensity could be tied to your grip strength: the stronger your grip, the higher the reasoning intensity. That way, you could work out harder to get higher reasoning intensity.

Alexandr Wang Says Muse Wonder Focused on Real-World Tasks for Real People

with muse wonder, we aimed to build a model that is useful for real world tasks for real people, informed by our product adoption and how people use muse. we focused on things that might not look as glamorous on twitter (for example, not 3d demo games), which in retrospect we probably could have done more of.

Alexandr Wang Says the Team Did Not Train Muse Wonder on 3D Demo Games

The whole team feels dumb now, but it's true: we did not explicitly train our model on 3D demo games. Obviously, in retrospect, we probably should've done a bit of that... but no regrets. Please try Muse Wonder on your actual coding work!

Meta releases Muse Wonder models with gains in coding and agent benchmarks

Meta released Muse Wonder and Muse Wonder Full, scoring 52 and 56 on the Artificial Analysis Intelligence Index v4.3, versus 48 for Muse Spark 1.3. Both support a one-million-token context window and text, image, video, and audio inputs, with stronger coding and agent results but weaker factual knowledge than leading competitors. Muse Wonder is available through Meta's API and Muse Code at higher prices than its predecessor; Muse Wonder Full is currently limited to Muse Code users.

The same story is shown in the picks as 《Meta releases frontier models Muse Wonder and Muse Wonder Full》

we are working to resolve a bug in how muse wonder and muse wonder full are counting against usage limits for Muse Code subscribers this is not intended behavior -- we will update everyone once we have fixed it and issue resets

we are working to resolve a bug in how muse wonder and muse wonder full are counting against usage limits for Muse Code subscribers this is not intended behavior -- we will update everyone once we have fixed it and issue resets

How to Teach GitHub Copilot About Your Codebase

GitHub’s beginner guide explains four ways to tailor Copilot to a project: custom instructions for repository conventions, agent skills for repeatable procedures, custom agents for broader specialized tasks, and MCP servers for connecting to external tools and data. It recommends starting with a convention you often explain and adding it to `.github/copilot-instructions.md`.

Already showing people what they can build with Codex? Applications to become a Codex Ambassador are open again. We support you in hosting meetups or sharing what you’ve learned: https://t.co/qNrrcEL7sN https://t.co/31ILHSgUz1

Already showing people what they can build with Codex? Applications to become a Codex Ambassador are open again. We support you in hosting meetups or sharing what you’ve learned: https://t.co/qNrrcEL7sN https://t.co/31ILHSgUz1

Artificial Analysis launches FrontierCode 1.1 leaderboard measuring maintainer-ready coding changes

Artificial Analysis launched its FrontierCode 1.1 leaderboard, evaluating models on Cognition’s private coding benchmark using the 100-task Main set and its Stirrup open source reference harness. Grading combines unit tests with maintainer-oriented criteria; failing any blocking check yields zero. Claude Opus 5.5 (max with fallback) leads at 52%, with blockers passed in 58% of attempts; MiMo-V2.6-Pro leads open weights models at 45%, while GPT-6.1 Sol (max) scores 49% at $0.81 per task, matching Claude Fable 5.1 (max with fallback).

Meta releases Muse Wonder and Muse Wonder Full with higher benchmark scores

Meta has released Muse Wonder and Muse Wonder Full, according to Artificial Analysis in the post quoted by Alexandr Wang. At max reasoning effort, they score 52 and 56 on the Artificial Analysis Intelligence Index v4.3, compared with Muse Spark 1.3’s 48, following a release gap of 6 weeks. Muse Wonder is available through Meta’s first-party API and Muse Code, while Muse Wonder Full is limited to Muse Code users; both have 1M-token context windows.

Meta releases frontier models Muse Wonder and Muse Wonder Full

Meta’s Superintelligence Lab released Muse Wonder and Muse Wonder Full on Monday, larger models described as more capable than Muse Spark. Meta reports benchmark scores comparable to Fable 5.1 and GPT-6 Astra and emphasizes information retention through “active memory.” Wonder costs $4.00 per million input tokens and $20.00 per million output tokens through the Meta Model API; Wonder Full is available only to Muse Code subscribers. Both models will power the Muse agent.

Meta releases Muse Wonder and Muse Wonder Full with higher Artificial Analysis scores

Meta has released Muse Wonder and Muse Wonder Full, which Artificial Analysis reports score 52 and 56 on its Intelligence Index v4.3 at max reasoning effort, versus 48 for Muse Spark 1.3 (max). Muse Wonder Full improves across all ten evaluations, with the largest gains in agentic evaluations. Muse Wonder is available through Meta’s first-party API and Muse Code at launch, while Muse Wonder Full is limited to Muse Code users; Muse Wonder costs $4.52 per Intelligence Index task.

The same story is shown in the picks as 《Meta releases Muse Wonder and Muse Wonder Full with higher benchmark scores》

Already showing people what they can build with Codex? Applications to become a Codex Ambassador are open again. We support you in hosting meetups and sharing what you’ve learned: https://developers.openai.com/community/codex-ambassadors

Already showing people what they can build with Codex? Applications to become a Codex Ambassador are open again. We support you in hosting meetups and sharing what you’ve learned: https://developers.openai.com/community/codex-ambassadors

MUSE WONDER 🍉 muse wonder is the best model in the world for personal agents and professional agents. we evaluated our model against the best models in the world across agentic and coding tasks, and we think you all will like it.

MUSE WONDER 🍉 muse wonder is the best model in the world for personal agents and professional agents. we evaluated our model against the best models in the world across agentic and coding tasks, and we think you all will like it.

Clearing chat history helps AI agents find better solutions

A Microsoft Research study reports that Fork-and-Flush helps long-running AI research agents explore better solutions by creating parallel branches that retain workspace files but discard chat history. Across 13 tasks with the same compute budget, it achieved a min-max-normalized average score of 0.78, versus 0.47 for single runs and 0.54 for best-of-4. The researchers found that accumulated context can trap agents in similar approaches, even when conversation histories are periodically compressed.

Andrej Karpathy describes a widening gap in how people experience AI capabilities

Andrej Karpathy describes four tiers of LLM exposure, arguing that public perceptions lag behind capabilities experienced by frontier-system users. He estimates roughly six billion people have barely encountered LLMs, one to two billion use casual chatbot products, 20 million use frontier models professionally in math and code, and 5,000 access internal frontier systems. He claims those internal systems coordinate thousands of agents on projects that would take experts years, while human review falls behind, and attributes progress in coding and math to reinforcement learning on verifiable rewards and commercial training priorities.