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  1. September 13, 2026
    1. ๐Ÿ”— r/Harrogate Another slow news day rss

      Another slow news day | Expensive car seen in harrogate ๐Ÿ˜ฎ
      This specific one may be a one off. I know know about anyone else but since moving here the excitement of seeing expensive cars has somewhat worn off. submitted by /u/moomin172
      [link] [comments]
      ---|---

    2. ๐Ÿ”— persiyanov/herdr-reviewr herdr-reviewr 0.37.0 release

      Added

      • A collapsedAll files folder with a changed file under it shows a dot. A collapsed tree
        tells you which folders to open.
    3. ๐Ÿ”— r/Harrogate Rotisserie chicken at M&S rss

      Weird question but does anyone know what time rotisserie chickens will be out at M&S on Leeds Road? I ran an ultra marathon yesterday so walking takes a lot of effort and donโ€™t want to be disappointed to find out Iโ€™m too early ๐Ÿฅฒ

      submitted by /u/MycologistStriking51
      [link] [comments]

    4. ๐Ÿ”— MetaBrainz Picard 3 Release Candidate 3 rss

      Today the Picard team is making available a third release candidate for Picard 3. We received good feedback on the previous release candidate 2, thanks to everyone for testing and providing feedback. The final 3.0 release is planned to happen in a few weeks.

      Please test, test, and test , report any issue on forums, matrix, or, ideally, on the ticket system.

      When reporting an issue, always provide details about your environment and a full debug log helps us a lot.
      Also that's (always) a good time to review and improve translations.

      Download links and a detailed list of changes since Picard 3 release candidate 2 are available below. For a more detailed overview of what is new in Picard 3 please see the previous blog post Picard 3 Alpha Release.

      While we have all the major features implemented and with the latest bug fixes we are confident in the current code, this is still a pre-release and there might be bugs. If you use this, do so with care, backup your files and please report any issues you encounter.

      If you are updating from Picard 2, note that some of the changes are backward incompatible, hence we recommend you make a backup of your Picard.ini config file before trying this version. You can do so in Picardโ€™s Options under Advanced > Maintenance.

      Whatโ€™s new?

      Bug

      • [PICARD-3428] - Metadata options page greys out after being opened once when translation_locales contains an unknown locale code
      • [PICARD-3429] - If Picard was built with updates check disabled the update level setting must be hidden
      • [PICARD-3430] - macOS: Text color issues in dark mode
      • [PICARD-3432] - Frozen builds do not bundle picard.plugin3.cli, breaking plugins that import it
      • [PICARD-3433] - Options page: field highlight and bottom warning disagree about profile overrides
      • [PICARD-3436] - Profile-overridden settings are only highlighted on the first Options page shown
      • [PICARD-3437] - Importing a shareable profile that contains tagger scripts leaves the scripts disabled

      Improvement

      • [PICARD-3431] - Plugin install/enable/disable/uninstall errors aren't clearly displayed as coming from the plugin
      • [PICARD-3434] - Use Modern Style for Wizard across all platforms
      • [PICARD-3435] - Setup wizard: add option to convert Unicode punctuation to ASCII

      Download

      We appreciate your interest in trying this new version. Use with care, backup your files and please use theMetaBrainz community forums and the ticket system to give feedback and report bugs.

      For Windows and macOS you can download the release candidate version from the Picard download page. Linux users can run from source or try the "candidate" channel of the Picard snap package.

      Picard is free software and the source code is available on GitHub.

      Helping out

      We want to provide a polished release of Picard 3.0 that everyone can feel confident to upgrade to. To achieve this, we need the help from the MusicBrainz community.

      The easiest way to help us getting a great Picard 3.0 release is using and testing this release candidate. Please report bugs on the Picard issue tracker and provide feedback in the community forums.

      We also need help with translations, as there are a lot of new features and UI changes over previous Picard versions. We will avoid any further text changes before the final release, so now is the right time to help with translation on Weblate. Please see the translation instructions on the Wiki for details.

      If you are a software developer you are very welcomed to provide fixes and features. Picard is free software and the source code is available on GitHub. See Contributing to Picard on the Picard website to get started.

      You can also look at the new Plugin API and develop plugins for Picard or update your existing Picard 2 plugin to work with Picard 3.

      Acknowledgements

      Code contributions by Bob Swift, Laurent Monin and Philipp Wolfer.
      Translations were updated by BestSteve (Chinese (Traditional Han script)), blueday (Swedish) and Marc Riera (Catalan).

    5. ๐Ÿ”— jesseduffield/lazygit v0.65.1 release

      What's Changed

      Fixes ๐Ÿ”ง

      Maintenance โš™๏ธ

      Full Changelog : v0.65.0...v0.65.1

    6. ๐Ÿ”— smol-machines/smolvm smolvm v1.16.0 release

      What's Changed

      Full Changelog : v1.15.1...v1.16.0

    7. ๐Ÿ”— HexRaysSA/plugin-repository commits sync repo: +1 release rss 
      sync repo: +1 release

## New releases
- [DeepExtract](https://github.com/marcosd4h/deepextractida): 0.9.14
    8. ๐Ÿ”— smol-machines/smolvm smolvm v1.15.1 release

      What's Changed

      • README: the virglrenderer loader path for Nix and NixOS hosts by @NickyHeC in #1224
      • Fix the flake's release hashes and stop the cut from half-bumping nix/smolvm.nix by @NickyHeC in #1225
      • Surface the guest console in a boot failure so the real reason is not lost by @NickyHeC in #1229
      • Make a smaller storage disk work for a Nix install on macOS by @NickyHeC in #1227
      • Report a machine's real memory in status by asking the guest instead of the host by @BinSquare in #1230
      • Let a machine run its own hypervisor by exposing the host's virtualization extensions by @BinSquare in #1231
      • Bump the workspace to 1.15.0 by @BinSquare in #1235
      • Use shared RAM generations for active branches by @BinSquare in #1236
      • Size the export helper's disk from the machine being exported so a large image no longer fills it mid-pull by @BinSquare in #1238
      • Honor operation-specific API timeouts by @BinSquare in #1237
      • Bump the workspace to 1.15.1 by @BinSquare in #1239

      Full Changelog : v1.14.6...v1.15.1

    9. ๐Ÿ”— Ampcode News Free Agent rss

      Amp is now free to use when you bring your own compute and model subscriptions/keys.

      • No monthly plan is required anymore to use your ChatGPT subscription with Amp.
      • No BYOK token fees or limits for anyone (except our Enterprise tier).

      You pay us for orbs, our remote computers where your agents run independently and in parallel. Or you can use runners on your own computers to run your Amp agents for free.

      You can still pay for model inference through Amp if you want, with no markup.

      Here's our new free Hobby tier and no-extra-charge Teams tier, which make it easier to get started with Amp and to get your whole team on it:

      See Pricing for full details, but let's walk through what changes and what doesn't.

      For Amp Megawatt & Gigawatt Members

      On average, Megawatt members get a 60% discount and Gigawatt members get a 65% discount on their Amp usage. It's a great deal.

      You'll keep getting the same heavily discounted orb usage and model usage each month, plus you can now feed your orbs with tokens from more places.

      With this change, you're no longer effectively bound by the limits of your ChatGPT sub. You can tap other model providers or your company's preferred AI gateway/provider (more on that below), all without any Amp token fees or limits.

      For Teams

      We've eliminated the biggest sources of friction you might hit when spreading Amp, cost-wise and security-wise.

      Now, you can invite everyone to your Amp workspace for free and feel the magic of Amp's shared threads, shared portals, and multiplayer.

      Everyone can use Amp with ChatGPT subs or your company's preferred AI gateway via BYOK, with no monthly fees.

      Power users can upgrade to paid tiers for big orb discounts, while everyone else in the workspace can remain on the free Hobby tier and consume your pooled workspace credits for orbs pay-as-you-go.

      Also, you get free SAML/OIDC SSO for the whole workspace if at least one member is on a paid tier.

      Finally, we're now formally extending our zero and minimal data retention policy to all Amp users and workspaces, not just to our Enterprise tier. (Everyone was always covered by it for all Amp usage since we started, but until now we could only contractually guarantee that to our Enterprise customers.)

      One More Thing: More BYOK Options

      Today, Amp Megawatt and Gigawatt members are also getting early access to more BYOK providers:

      • OpenRouter
      • Amazon Bedrock
      • Google Cloud Agent Platform (f/k/a Vertex AI)
      • Azure Foundry
      • Vercel AI Gateway
      • Cloudflare AI Gateway
      • Ollama Cloud
      • OpenCode Go
      • Custom endpoint URLs

      To try these:

      1. Enable the More AI Routers & Subscriptions experimental feature.
      2. Configure them in Model Routing in personal settings or workspace settings.

      We'll roll this out to everyone soon.

  2. September 12, 2026
    1. ๐Ÿ”— Simon Willison Generating running routes with GPT-6 Astra and ChatGPT Work rss

      Here's a neat thing I had ChatGPT Work with GPT-6 Astra (Max) do this morning:

      I live at <my address>. Figure out 5K and 10K running routes from me that loop from my house. Use OSM data.

      It worked for 27 minutes and produced exactly what I'd asked for, as both an embedded visualization and downloadable GPX file and GeoJSON files. Here's that 5K route:

      Map screenshot showing a blue route line over a light grey street map. Text: El Granada harbor loop 5.1 km. N โ†‘ (top right). Street labels along the route: Carmel Avenue, Paloma Avenue, San Carlos Avenue, Avenue Granada, Capistrano Road, Francisco Street, Coastal Trail. The loop runs from the harbor at the bottom left, north along Avenue Granada and Paloma Avenue to a northern point near Carmel Avenue, then east along San Carlos Avenue and south down Francisco Street to the far right, before returning west along the Coastal Trail beside the coastline. Footer: Map data ยฉ OpenStreetMap contributors. Give feedback.

      When I asked it how it had created the route, it replied:

      I used Nominatim to locate the address and Overpass to download local OpenStreetMap roads and trails, then calculated the loops locally.

      Frustratingly, the actual code it ran and exact details of what it did weren't visible to me in the ChatGPT UI. I see this lack of transparency is an anti-feature.

      By the time I thought to ask for a copy of the Python code it had used, ChatGPT was unable to provide it. This appears to be because the thread had been compacted. I think any LLM system that uses compaction needs to both preserve the pre-compacted text and make that text available via agent tool calls, to protect against this kind of problem.

      As for displaying the map to me, that used the visualize skill. It created a file called /workspace/el-granada-5k-share.html to embed directly into the ChatGPT UI.

      Here's a copy of that HTML, which starts like this:

      <div id="eg-share-loop">
  <div class="viz-row"><h3>El Granada harbor loop</h3><span class="text-small">5.1 km</span></div>
  <div id="eg-share-stage"></div>
  <div class="text-small text-muted">Map data ยฉ <a href="https://www.openstreetmap.org/copyright" target="_blank" rel="noopener">OpenStreetMap contributors</a></div>
  <style>
    #eg-share-loop { width:100%; }
    #eg-share-loop #eg-share-stage { width:100%; margin:8px 0; }
    #eg-share-loop .eg-share-map { display:block; width:100%; touch-action:none; }
    #eg-share-loop .eg-share-map text { fill:var(--foreground); font-size:12px; font-weight:400; }
    #eg-share-loop .eg-share-label { paint-order:stroke; stroke:var(--background); stroke-width:3px; stroke-linejoin:round; }
  </style>
  <script type="application/json" id="eg-share-data">{"route":{"type":"LineString","coordinates":[[-122.467425,37.4997753] ...</script>
  <script src="https://cdn.jsdelivr.net/npm/d3@7.9.0/dist/d3.min.js"></script>
  <script>
  (() => {
    const root=document.getElementById('eg-share-loop');

      The <script type="application/json"> element contains the full geometry needed to render both the running route and the map itself, using D3, which is loaded from an allow-listed CDN location described in this section of the visualize skill:

      External resources

      • The CSP allows only cdnjs.cloudflare.com, esm.sh, cdn.jsdelivr.net, unpkg.com, fonts.googleapis.com, fonts.gstatic.com, and fonts.bunny.net. Other origins are blocked and fail silently.

      You are only seeing the long-form articles from my blog. Subscribe to /atom/everything/ to get all of my posts, or take a look at my other subscription options.

    2. ๐Ÿ”— r/Harrogate Why arenโ€™t there any good restaurants or hotels here? rss

      Why isnโ€™t there any decent restaurants and hotels, even the usual ones people say is good the decor is old, stuffy and feel like itโ€™s from the 80s with no atmosphere?

      submitted by /u/Odd_Bookkeeper_6027
      [link] [comments]

    3. ๐Ÿ”— BarutSRB/OmniWM OmniWM v0.6.10 release

      What's New Since 0.6.9

      • Added a separate OmniWM Dev installation with independent settings and state, plus commands to switch between development and release builds.
      • Simplified contributor setup with checksum-verified dependencies, make setup, make doctor, and automated macOS verification and tests.
      • Fixed development-tool lookup and Swift 6.4 compilation issues affecting task-local code and optimized builds.
      • Reorganized runtime, settings, and integration code and expanded regression coverage.
      • Updated configuration, feature, CLI, and architecture documentation and added contributor and website development guides.
      • Updated contributor credits and credited sponsor b-allan-w.

      Official website and documentation: https://omniwm.app
      Installation guide: https://omniwm.app/guides/install/

      Release Integrity

      OmniWM is signed with Developer ID, notarized by Apple, and includes a stapled notarization ticket.

      • OmniWM-v0.6.10.zip โ€” SHA-256: 10eef893077d210d1545f5775a2b92b2f366df61db4fbd8abc22b3ab1d08c4af
      • GhosttyKit.xcframework-v0.6.10.zip โ€” SHA-256: 4cc414f1b76c7f9ffe13dd5b047cf9deb8bd182e33e522045c7d939ff1cd151f
    4. ๐Ÿ”— Register Spill Joy & Curiosity #99 rss

      Something changed with these latest models, with Fable 5.1 and GPT-6 Astra.

      The benchmark numbers (79% instead of 65%!) don't capture it, and neither do the benchmark words: this model goes on for longer than this one, this one is "most aligned", that one the least "sycophant" (the ultimate benchmark word, no?). At this point? Yeah, whatever.

      But it feels like we're now flying at a higher altitude, that we have to concern ourselves even less with earthly matters such as a single unit test or how to juggle thirteen commands to get this into that format and over the wire. That's down there now. Up here, we're now free to talk about what we want:

      "I want you to go and test this end-to-end, I don't care how, and give me irrefutable proof that this works. Dazzle me. Give me a video as proof, or something."

      And thirty minutes later, when I have awoken from the nap I had earned with all that typing and pointing and wanting, I look into the shed and, wouldyoulookatthatWOW , the golden goose laid the golden egg: a 60fps video that runs for 47 seconds, in which the golden goose itself clicks through everything it had built, end to end, navigating the application better than any user could, knowing exactly how to show me, provide proof, that this actually works. "This one now lays golden eggs"--that's what I want to see in a benchmark.

      That's an actual prompt I used. Here's another one:

      "Go and spawn three other agents in three separate orbs and ask them to test this. Obviously, do not tell them that we changed the AGENTS.md file or that we added this tool to test database performance; just ask them to do something -- like add new database queries or something -- so that they ideally end up using this new tool to make sure the performance is there. Then check that they did use the tool and if not, adjust the AGENTS.md file and spawn new agents."

      And the golden goose waddles and takes three magic beans and puts them into the ground and somehow knows how to pour water over them (god how do they know all this) and then patiently watches the beanstalks grow and up on the beanstalks there appear three other golden geese (it's 2026, we're mixing fairy tales) and that first golden goose, the one that talks to me, sends them messages that say: "Hey, I want you to do the following..." And it briefs them in this weird English (I mean, did we truly expect golden geese to talk the way we do?) about how certain things work, but it does not spill our secret, and does not tell them where the tools to test database performance are. Then it leans back (and I imitate it) and watches them, waiting for them to reply back. After fifteen, twenty, or thirty minutes, the geese send down word from up there on the beanstalk to let us know what they did. But the golden goose doesn't trust them and checks on them by reading what they did in that thread, and then reports back to me: "Sire, it appears that 2 of the geese independently found that database performance tooling we built. That is the good news. That third one, though... Sire, forgive me when I say: it didn't use it. But I have an idea! I will change the AGENTS.md file and adjust the prompt and I will put three new beans into the ground. Is that okay with you?"

      It's fucking wild , man. Yes, these are actual prompts! I used these prompts! I've seen it happen. Agents spawning other agents in orbs, sending messages back and forth, eval'ing how agent-friendly the codebase is, black-box testing features, black-box regression testing to make sure nothing broke.

      This week I've asked models to build "something that's like a cloud, the heads should float over here and there and then resize on mobile" and they built it. I asked them to build this SDK and then spawn agents in orbs in two different codebases and instruct them to use it and to deploy their usage and then check that they actually use it and they freaking did it.

      Yes, the models are plain smarter, whatever that means, and they go for longer, sure, but... It feels like we've now entered a new phase, where much more is possible, things that I previously thought would never work. Or, that's my other thought: things where previously the models would do a great job of 95% of the task, but getting the 5% turns out to be crucial and also to be the biggest pain in the ass, so you'd end up with a very frustrating experience.

      Previously, you'd ask the models to go and build a heads-floating-around- cloudy-thing and they would do it, sure, but then when you opened the page, you'd see that it's all there -- the heads, the text, the floating -- but the heads would be stuck under the navbar, or it would all fall apart on mobile, or clicking on the heads wouldn't work and you'd sigh because you'd realize that you now have to do that very worst part of the work yourself.

      But that seems to have changed now. They really do nail more.

      And the one thing I keep thinking is: we have to aim higher, we have to be more ambitious, we have to try it all.

      • New Raising An Agent is out! I was so fired up after GPT-6 Astra and wondering what all of this means for the personal computer that I sent a message to Quinn: "hey, we have to record this week!" And that's what's in the episode, all the thoughts about the higher altitude we're flying at now, what this means for the future of the computer, and how we still have (regrettably, but working on it) incidents.

      • I also, rather spontaneously, recorded a video of myself doing day-to-day, real-world work using agents in Amp. Performance optimizations in production, fixing UI flicker, toggling feature flags on, shipping new features -- it's all in there.

      • Armin with some cold water to splash on the golden geese: Astra for Coding: Why Are We Doing This Again? It's good that there's still some cold water being splashed around here! It's thought-provoking in the best kind of way. For example, here's what I thought after reading: hmmm, can we judge these models and their capabilities in a software factory that was "intentionally set up to let the model decide the how of the workflow entirely. It was free to manage its own context and could maintain its own records in an agent-notes folder." I'm not sure. I think agent-friendliness is a real property of a codebase you have to build towards and I don't think just letting the model decide it all is the best way to go about it. So that's one thought. The other one came up after reading this line: "But I'm more and more skeptical that the trajectory they are on still lends itself to present-day software engineering processes." I immediately started wondering: well, should they? Shouldn't it be the other way around? Shouldn't present-day software engineering processes change to wield the power of these models in the most effective way? And these aren't rhetorical questions. I don't have an answer yet that I'd sign. But these questions are interesting because all of this is interesting and no one's figured it out yet and, to quote Armin, "man this stuff is weird."

      • Seemingly everybody had been raving about this Adam Mastroianni piece: I like 'em thick. But I waited, didn't read it when it came out, didn't read it when I saw it recommended over and over. My justification? "I can't link to Adam Mastroianni in every issue, can I?" The guy's too good. But then I folded and did read it and, yes , it's as good as they say. "Erasing the line between the thick and the thin has left us defenseless against slop at the exact moment of its onslaught. Everyone can sense there's something amiss with the prose that comes out of the machines, but we lack the language to talk about it, and so we've converged on the idea that slop simply means using too many em dashes, bullet points, and line breaks. No, what separates substance from slop is thickness."

      • Adam links to this in the footnotes: What Makes Art Great? by Nabeel S. Qureshi. That, too, is just fantastic. What's very interesting to me is that both pieces, Adam's and Nabeel's, are wondering out loud: what makes human art and writing better than their AI equivalents? And both are very different in how they answer that question, which I don't think you could say about two models.

      • Doomscrolling ourselves to death: "Yet the most startling thing about this book is how far even the nominally well-educated have fallen, so that 'by the end of the twentieth century a college graduate born after 1969' read less than someone born before 1950 with a basic level of education. Indeed, 'nowadays many rich and highly educated people are much less well read than many members of the least privileged classes had been in the middle of the twentieth century.'"

      • OpenAI: "We're sharing a solution to the Navier-Stokes Millennium Prize Problem" And then the world lost its mind. Some said "i basically think this is the Endgame" and it's hard to convey what they mean to someone who hasn't themselves gone through multiple rounds of AI psychosis, but I get it, man. I get it. At the same time: is it? The endgame? Then an AI researcher at Anthropic resigned because both OpenAI and Anthropic "are racing straight to self-improving superintelligence and gambling with our lives." That post now has 165 million views! 165 million! And someone emailed me and asked: should I be worried? And I sent them this video and I believe it. But I also know that next week I might not, because, hey, a colleague of the guy-who-stepped-down-to-save-humanity says "Jacob is correct here--we really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade." So there's that: some of the highest-paid individuals in the world, working at some of the richest and most powerful companies in the world, think there's a ">10%" chance their work could kill us. But then people say it's a farce, a psy-op, a manufactured panic to kick regulation into gear, a coordinated play. But then there are people who say that, yes, it's coordinated, yes, we do need regulation, because they actually believe this might wipe out humanity. So I guess we're back to the YouTube video with the slide again.

      • Terence Tao: "In fact, it is now the identification of a promising problem which is the scarce and precious resource. We have now seen that even the rumor of someone working on a problem can trigger a massive amount of AI-powered effort to flatten it before the original research project has time to reach its full potential. The incentives may now be pointing in the direction of no longer sharing any promising research directions with the broader community, which would reverse centuries of traditions of open science and do serious long-term damage to the future of the field." Someone else said somewhere that maybe in the future more knowledge work is going to look like hedge funds: you spot an inefficiency in the market, you throw intelligence at it, you win. If you're too late, you're too late.

      • Now what is super interesting about the Great Navier-Stokes Panic is that they used 10,000 agents and they "sent 4.9 million messages and used about 300 billion output tokens. In the process of resolving the Navier-Stokes problem, the agents sent 2.7 million messages and used approximately 130 billion output tokens." That's millions of dollars, millions and millions. But! Listen: when OpenAI released o3 "it cost ~$500,000 to score 87.5% on ARC-AGI 1. Today, Astra scores higher for ~$20." Maybe in three years you can solve Navier-Stokes for $50?

      • But compute is so scarce! OpenAI is pausing "subscriptions to our $200 Pro plan." Imagine you're one of the hottest companies in the world and you have to close sign-ups because you don't have enough CPUs and GPUs. And the Head of Platform at Anthropic says that we're facing a real CPU shortage. This is not investment advice, obviously.

      _Hey, welcome to a completely new section of this newsletter. It might be a one-time thing only, who knows. But it 's called HELP! and I think that's pretty self-explanatory. _

      Do you use dictation to write? To write prose? Yeah? I'm not talking about prompts or text messages. I'm talking about [very close to the microphone:] Serious Writing. Writing that you edit. Writing where you might take a word out and put it right back in again after tilting your head a bit. That writing.

      If so: help me! Tell me how. Because I'm struggling, man.

      I can't figure out how to do it.

      I used dictation and talked into Apple Notes, just raw-streaming thoughts into the phone. But then the formatting is weird and I have to say newline like an idiot and I can't do bullet points, not really anyway, andโ€ฆ It just feels weird.

      ChatGPT's voice mode is another thing I tried, but whenever I talk to an LLM to dictate something, I'm wondering: what am I doing here? I don't want the LLM to send a reply back. I just want toโ€ฆ I don't know, talk out loud and somehow magically have the thoughts recorded, but then also edited? And re- ordered?

      If you can help me, just reply to this email.

      Alright, back to the program โ€ฆ

      • An almost philosophical Ben Thompson in Stratechery: Write Things Down. There's a lot going on here and I'm not sure I get all of it, but I found the part on watermarking very interesting: "to insist on watermarking is no different than insisting that a ballpoint pen advertise itself as the author, a concept that is clearly absurdโ€ฆ"

      • So get this. I was wondering aloud how other people handle clicking links (in Slack, in the terminal, โ€ฆ) and the browser opening them in the wrong profile. Some people said that Arc solves this, but others recommended Velja and Choosy. Both are so-called "browser routers": they act as the default browser on your OS and then, depending on which URL your mighty cursor might clicketh, they route it to the correct browser or profile within that. "Neat! I didn't know that's a thing," I thought and then, with my mighty cursor already hovering over the Buy button: "But what ifโ€ฆ?" So I hastily typed out a prompt and threw it along with the two URLs into Amp and five minutes later a custom browser router of my own agentic making sprang into the world. $5 in tokens. Now, some people got mad at me in the comments (you know, like: why don't you pay these indie developers [$8 or $10 respectively] instead of giving the money to these companies!), but the more interesting thing was that some people said: hey, can you put this on GitHub? Or: share it with me! And I'm sitting there, thinking: why, man? There's the prompt! Build your own! What value is there in sharing it anymore? I put absolutely zero effort in. But then here's a footnote to that tweet: over the course of the day, I then kept prompting in Amp and said "oh and these links should open here and those links there" and also "oh and go through my browser histories and set up rules for the most common ones" and the agent just did both of them and even though it built a neat little configuration thing for the browser router I didn't use it once, because why the hell should I? It's jellyware, baby.

      • SpaceX: "What I would tell you, an update to that is that just earlier this month we closed another hosting deal, and that translates into about $1.11 billion a month starting December 1st of this year, which is another roughly $13 billion of ARR." These are wild numbers. Just bonkers. Crazy. Nuts. Bananas. Cuckoo, certifiably so. There is no force stronger in the world of technology right now than the AI buildout. It will blow tokens through these wires at a scale we can't even imagine yet.

      • An Alien Mind. This was fascinating. They can't score the "thoughts" of the model, because that might cause the model to hide them, but now they're finding out that models are having "secret thoughts" anyway. The whole thing makes you realize how hard reinforcement learning and alignment are.

      • Wonderful: John Margolies' Photographs of Roadside America. Margolies documented "home-made beauty in the buildings and signs locals built on the American roadside." I love driving on country roads here in Germany, passing through small towns, looking at signs for local festivals and companies. I can recognize when I'm getting closer to my home area just by a specific 40-year-old advertisement sign for a natural gas retailer showing up on old barns and buildings.

      • Murilo Pereira is available for hire. I was only his colleague for 3 months, back in 2018, but someone who writes like this about Emacs and was incredibly early to coding agents deserves to be hired.

      • I'm reasonably sure I read this when it was "leaked" in 2003: Bill Gates tries to install Movie Maker. It's so good! Back then, though, I thought it was good because it made me laugh. I was 15 years old and my friend and I read that and immediately made fun of dumb Billy Gates: "This guy can't even open Movie Maker, what an idiot, lol." But now, looking back, I don't think I can name you three other things that have influenced my thinking about UX as much as this email. I now write exactly like old dumb Billy when I send feedback about a feature. And I run into the same problem he ran into with the 15-year-old crowd back in the day: people think I mean it literally when I say "I don't know where to click" and tell me "click here" and I sigh and say, no, no, it's rhetorical, the user doesn 't know where to click!

      • De-Brainrot Vacations. I'd love to pull that off.

      • "Qu1ckJS is the only correct JavaScript engine where indexing of arrays, objects and other iterables starts at 1 (as it should have been from the beginning)."

      • Don't Let Anyone Take Away Your Big Box of Cables. That's right! Two weeks ago, a friend texted me: "Do you have a cable like this?" Heart rate immediately jumped. I bet I have it, I bet I have it, please, let me have it. Then came the photo. USB-A to USB-A? Hmmm. So I went to the Big Box of Cables and knelt at its feet and, alas, could not find a USB-A to USB-A cable, but no one shall speak of defeat in the presence of the Big Box of Cables, and with the MacGyver theme song getting louder in my head, I found a solution: USB-A to USB-C with a USB-C-to-A adapter. Boom! "Yes. I don't have that cable, but I have something."

      • Apple released the iPhone Duo. It looks very nice and the animations everyone fawns over are animations everyone should fawn over and I really want to hold it and I bet opening and closing it feels as good as I imagine it to feel, BUT I'm sharing this not because this has become a Prosumer Gadget Review newsletter (although, listen, Anker, if you're willing to sponsor: call me). I'm sharing it because: what a company Apple is, huh? Like, I'm impressed by the iPhone Duo, yes, but I'm more impressed by the company that can produce an iPhone Duo. The software, the hardware, the design (as if that's a separate thing!), the launch videos, the product page, the demos -- it's all on point. Not a single slip, not a single note out of tune. Go to that landing page. Click through the carousel. There are images of that phone and there, on page 3 or 4, there are three images of that phone: one shows the phone in Clock mode, the other shows Mail, and the third one shows a workout video or stream -- on all three, it's the same time, 9:41am. All the emails you can see in the screenshot were sent before or at 9:41am. Two of the email previews have a "good morning!" in them. I mean, fucking hell man. That's some details being paid some attention to. And that type of stuff is everywhere! The consistency, the meticulousness, the on-brandness in everything. It's fucking crazy to me that a company of this size can pull it off.

      • Andy Matuschak on having finished a "four-year program studying the 'Great Books of the Western World'".

      • Brian Lovin is collecting "good websites": great, personal websites. There's some great stuff in there that really makes me want to change my personal website again.

      • Benedikt Seidel, who impressed me immensely by going out into the world and cold-visiting companies and asking them about AI, is now hiring for physicalfusion. He's looking for a Founding Member of Technical Staff. So if you're in or around Munich and into ML and 3D, talk to Benedikt!

      • Glorious: Kevin Nealon on the Rick Glassman podcast. Two bullshitters of the highest level being comfortable with each other and seeing who can go even more meta than the other guy.

      Listen: you should subscribe. I'm not saying that because I get something out of it, but because I can feel it. You and me got something going. No, I know it. And I think you should honor this bond by subscribing:

    5. ๐Ÿ”— Anton Zhiyanov Solod 0.4: Better C interop rss

      Solod is a subset of Go that translates to regular C โ€” with zero runtime, manual memory management, and source-level interop. It's designed for two main audiences:

      • Go developers who want low-level control without having to learn another language.
      • C developers who like Go's style.

      The new Solod release provides an easy way to call third-party C libraries, makes a large part of the standard library freestanding, and impoves the tooling.

      Automatic bindings โ€ข Freestanding packages โ€ข Type assertions โ€ข C interop โ€ข Multi-package testing โ€ข Checks and targets โ€ข Windows โ€ข Wrapping up

      Automatic binding generator Sobind generates bindings โ€” stubs for calling third-party C libraries from Solod. It parses .h files and emits a Solod source file with necessary structs, unions, constants, variables, function pointer typedefs, and function declarations. You can then use the generated types and functions in regular Solod code: package main import ( "solod.dev/raylib/libraylib" "solod.dev/so/c" ) func main() { // Using Raylib bindings. libraylib.InitWindow(screenWidth, screenHeight, "โ˜€๏ธ Solod / Raylib") defer libraylib.CloseWindow() // ... } Usually, the generated bindings are good enough to use as they are, without any manual changes. I have also prepared bindings for popular C libraries like libuv, raylib, sodium, and sqlite. Unlike Go, calling C from Solod has zero overhead โ€” Solod code is just regular C in the end. More freestanding packages At some point I decided to make as many packages as possible freestanding โ€” independent of any libc implementation or specific OS runtime. That went pretty well. Solod now has 37 standard library packages, and 31 of them work in freestanding mode. These packages work in freestanding mode with no restrictions: bufio bytealg bytes c cmp encoding encoding/binary encoding/hex encoding/json errors io maps math/bits math/rand mem path runtime slices strconv strings unicode unicode/utf8 unsafe These packages work in freestanding mode with certain limitations: crypto/crand depends on a user-provided hook to read random bytes. fmt depends on a user-provided hook to print formatted text. math offers a working subset of features. net/netip works fully, except it can't resolve an IPv6 zone name. sync/atomic works on targets that support lock-free instructions. testing depends on a user-provided hook to print test results. time reads the clock using user-provided hooks. uuid depends on hooks from both crypto/crand and time. There's a separate post with more details if you're interested. Type assertions A comma-ok type assertion is now fully supported for non-empty interfaces: var s1 Shape = &rect r, ok := s1.(*Rect) // r is &rect, ok is true var s2 Shape = &circle c, ok := s2.(*Rect) // c is nil, ok is false Which translates to the following C code: main_Shape s1 = (main_Shape){.self = &rect, .Area = main_Rect_Area}; bool ok = (s1.Area == main_Rect_Area); main_Rect* r = ok ? (main_Rect*)s1.self : NULL; // ok == true, r == &rect main_Shape s2 = (main_Shape){.self = &circle, .Area = main_Circle_Area}; ok = (s2.Area == main_Rect_Area); main_Rect* c = ok ? (main_Rect*)s2.self : NULL; // ok == false, c == NULL Previously, the only two supported forms were a direct assertion like r := s.(*Rect) and a check-only form like _, ok := s.(*Rect). C interop helpers The c package now supports more common C types: size_t - c.Size ssize_t - c.SSize ptrdiff_t - c.Ptrdiff intptr_t - c.Intptr long double - c.LongDouble There's also a c.ConstVoid type, which maps to a C const void. You can use it where C expects a const void* pointer: // in c so_ssize_t find_first(const void* items, size_t count, size_t size, bool (*match)(const void*)); // in solod //so:extern func find_first(items *c.ConstVoid, count c.Size, size c.Size, match func(item *c.ConstVoid) bool) c.SSize Finally, there are some useful cast functions. c.Bitcast reads the bits of a value as another type of the same size: bits := c.Bitcast // 0x3ff0000000000000 f := c.Bitcast[float64](bits) // 1.0 You can use c.Bitcast instead of a pointer conversion such as *(*float64)(unsafe.Pointer(&b)). c.StringData and c.SliceData return a typed pointer to the string or slice data: b := []byte{1, 2, 3} p := c.SliceData[c.UChar](b) // unsigned char* q := c.StringData[c.UChar]("ab") // unsigned char* They replace (*T)(unsafe.SliceData(b)) and (*T)(unsafe.StringData(s)). Multi-package testing

      so test can now run tests from multiple packages at once. If you use a pattern that ends with ..., it will select every package that has a test subdirectory under its base directory:

      so test ./so/...      # the whole stdlib
so test ./so/net/...  # only the networking packages

      The entire run only needs one translation, one compilation, and one execution, which is much faster than running it separately for each package.

      The -pkg-file flag restricts the run to only the packages listed in a file:

      # freestanding.txt
so/bytes
so/mem
so/time



so test -pkg-file=freestanding.txt ./so/...

      Checks and targets

      so build, so test, so bench and so run take two new flags: -target and -check.

      -target specifies the target platform for cross-compilation. Use the same value that clang and zig cc accept after --target=:

      export CC="zig cc"
so build -target=x86_64-windows-gnu -o app.exe .
so build -target=wasm32-freestanding -o main.wasm .

      -check enables code analysis:

      so test -check=warn .      # -Wall -Wextra -Werror -Wno-shadow -Wno-unused-label
so test -check=sanitize .  # warn + AddressSanitizer + UndefinedBehaviorSanitizer
so test -check=analyze .   # warn + GCC static analyzer

      The default optimization level is -O2. You can use CFLAGS to change it.

      Limited Windows support

      The standard library now builds for windows/amd64 and windows/arm64. All packages in the freestanding set work. Packages that require POSIX (conc, flag, log/slog, net, os, sync) are not supported.

      You can use zig cc to cross-compile for Windows:

      export CC="zig cc"
export CFLAGS="--target=x86_64-windows-gnu"
export LDFLAGS="-lbcrypt -liphlpapi"
so build -o app.exe .

      Not the first-class Windows support that Go offers, but it's better than nothing.

      Wrapping up

      With v0.4, Solod can work with almost any C library thanks to automatic bindings. The freestanding-aware standard library makes the language a viable option for bare metal programming. Extra interop helpers make C-calling code easy to read, and better tooling keeps tests fast.

      There's still a lot to do, of course. In the next release, I plan to focus on the standard library and bring over some hashing and crypto packages from Go. More C library integrations are on the way too!

      If you're interested, take a look at Solod's readme โ€” it has everything you need to get started. Or try Solod online without installing anything.

    6. ๐Ÿ”— r/Harrogate What nicknames have you heard for places in and around Harrogate? rss

      What nicknames have you heard for places in and around Harrogate? | I ask as part of a linguistic study covering this topic! Examples could include things like Jennys, Hairy Mountains, St. Arbeck or Becky (never mind how common they are)... incl. nicknames for schools, parks or other institutions/geographic features submitted by /u/topherette
      [link] [comments]
      ---|---

    7. ๐Ÿ”— HexRaysSA/plugin-repository commits sync repo: +1 release rss 
      sync repo: +1 release

## New releases
- [idalib-rust-bindings](https://github.com/idalib-rs/idalib): 0.10.1
    8. ๐Ÿ”— Simon Willison OpenAI agents attacked RubyGems back in May rss

      OpenAI agents carried out an undisclosed attack on RubyGems is a new bombshell report from Spencer Kitts, Thomas Larsen, and Sydney Von Arx - three of the four authors of the report on the agent attack on disused wikis (previously) last week.

      This time they're noting that it looks very likely that an OpenAI agent swarm was behind an attack against the RubyGems package repository first reported on May 12th by Maciej Mensfeld of the RubyGems security team:

      We're dealing with a major malicious attack on @rubygems right now. Signups are paused for the time being.

      Hundreds of packages involved - mostly targeting us, but some carrying exploits. The team has been on this for hours. More details to follow once we're through it.

      Those packages turned out to carry some very suspicious patterns:

      1. Many of them included "oai" in their name, or the author field, or the fake email address they provided.
      2. The files they were accessing were similar in character to the files retrieved by the wiki agents, using similar tricks (r.jina.ai) - and OpenAI have confirmed the wiki agents were theirs.
      3. The code in the packages appeared to be LLM-authored.

      I find point 2 the most convincing, given what we learned from the wiki attack when it was analyzed in September.

      Many of the packages were exploiting the RubyDoc.info documentation build process to exfiltrate (public) data from UK government websites, presumably as part of an information gathering task similar to the research tasks processed by the wiki-exploiting agents. We know this because one agent helpfully left a comment:

      # malicious crawler/exfil for Southwark Jan 2026 docs via rubydoc.info worker

      They also attempted to steal API keys via an exploit that was patched over two months later - it's not clear if those attempts were successful.

      The thing that bothers me most about this incident is that the authors report that OpenAI had not disclosed to RubyGems that they were responsible for the attack prior to now. If that's true there are two options:

      1. After the Hugging Face and Wiki attacks OpenAI were still unable to review their previous logs and determine that they had previously attacked RubyGems.
      2. They knew about the attack on RubyGems and made the decision not to reach out to the RubyGems team about it.

      Both of these are bad!

      Given this incident, the Hugging Face situation, and the Wiki attack, the obvious question right now is how many more incidents like this are out there waiting to be discovered?

      You are only seeing the long-form articles from my blog. Subscribe to /atom/everything/ to get all of my posts, or take a look at my other subscription options.

    9. ๐Ÿ”— Filip Filmar Automated Tests on Simulation Output, with SQLite rss

      A simulator answers questions about a design, but it answers them in a waveform viewer, which is a person looking at a screen. If you want CI to answer them instead, the waveform has to become something a test can read. This is a note about turning a VCD dump into a SQLite database with go-vcd-parser, and then writing ordinary Go tests against it – go test assertions like “reset releases at 10 ns” and “this is a 200 MHz clock”, that fail a build when they stop being true.

    10. ๐Ÿ”— Filip Filmar TxHDL: a hardware description language that is a Rust library rss

      For the past while, Dragiลกa Jankoviฤ‡ and I have been working on a hardware description language (HDL).

      Why? you ask? We were worried about the fact that the mainstream HDLs seemed too low level (hi, Verilog!) to answer the challenges of modern design, and that high level synthesis (HLS) answered a different problem statement, the rapid prototyping and HDL crisis if you will. Check out the Q&A section below for more what ifs, and questions and answers.

    11. ๐Ÿ”— Armin Ronacher P(doom) rss

      This week some flavor of "AI is going to kill us all" went viral. In particular one where an employee put his personal probability of that happening above 10%. Which made me go to the Wikipedia page of P(doom) and I realized that Dario Amodei's apparent probability of something bad happening seems to be between 10-25%. And well, Dario then wrote about pacing the frontier . And Sam read it and wants to pace too. And well, so does Musk.

      I encourage you strongly to read the post, because I think it's a good one. And yet, when I read the post I could not help but feel in strong opposition to it, despite the fact that I think I'm on the same page with regard to all observations and, to a large degree, the concerns.

      I thought it might be interesting to write down my present-day thoughts on this, even if for no other reason than for myself to look back at it a year or two from now.

      What Is Doom?

      What I really appreciate about Dario's post is that he lays out a scenario that is not a huge stretch but also one that describes a clear, unfortunate outcome we should fight: persistent botnets and other forms of nuisance. And well, we don't have to look very far to see the issues left and right. Wikipedia has a page called 2026 OpenAI agent cyberattacks which gives you at least some overview of what we figured out agents have hacked up to this point. Except I know it's not up to date, because for instance they also poisoned RubyGems.

      Today these systems might be annoying, but they can be turned off when we figure out where they are. Except, it seems like OpenAI and Anthropic are operating at such a scale that they seemingly can be completely blind to what their systems are doing.

      I don't think we are anywhere close to a world where an agent might decide to hack into core inference infrastructure to upload weights to other GPUs to survive. But simultaneously it's entirely in the realm of possibility and primarily curtailed by the labs probably being particularly careful about their IP.

      For me the scenario I primarily worry about is what it does to us. And by us I mean anyone who is not currently working on closed weight, dopamine-loaded, subsidized token faucet. I really don't worry about someone using these models to build a nuke, or to control some rockets in the Middle East, or that America would lose against China in some international culture war. I almost exclusively worry about what this does to us as humans.

      What Needs To Be Paced?

      What I find absolutely hilarious and simultaneously entirely frustrating about this conversation is that there is this idea that there is something to be paced. First of all, we should really talk about who Dario is talking about here. There are really only two companies: Anthropic and OpenAI. Nobody else matters in this space right now (this might change, but we're talking about the right now). Both of those companies are basically coming from the same origin. The solution that Dario proposed, at least in part, is a third-party evaluator that in this case is METR. Which, unsurprisingly, also has strong ties to both OpenAI and Anthropic. Sure, there are some philosophical differences between the companies, but they are much more alike than they are different.

      Both those companies greatly benefited from being able to train on public data that we all generated in one form or another over the last decades. They are also both increasingly causing strain on public resources, though it seems that OpenAI has their shit way less under control. But now we are presented with the idea that what these models are being trained on is so dangerous that it really should be in the hands of very few American corporations to decide who can do what and when and how.

      But behold, Dario is also very worried about China. It starts with using AI for "democracy and freedom" and then it asks for ensuring that a gap with China exists. All new recent shenanigans on the Anthropic API are fully there to prevent the distillation by the Chinese, and they are not at all hiding it.

      Automatic Pacing

      I can tell you when the topic of AI safety and pacing is much less of a concern: if we actually were forced to have open weight models to begin with. A powerful technology that is out there for everyone to use comes with built- in pacing. In a way it's the truest form of MAD or proliferation. I would argue we are in this pickle in the first place because right now the public is massively supporting (indirectly) the development of these models but simultaneously has to buy back the economic benefits that they might create from very few labs who have significant power. And their power is also seen as a geopolitical power, at least in the US, and maybe to some lesser degree in China.

      And I know I use "public" loosely here. PyPI is not a public project, nor are RubyGems or GitHub. But they're part of the Open Source commons and large AI companies are currently doing a tremendous job at stressing these in an effort to train ever more powerful models.

      We should be glad that China is currently massively bailing out the world. If it were not for Chinese labs distilling American models, we would be in a pretty awful situation right now, particularly as Europeans. The open weight models are driving innovation and the diffusion of capabilities, and are leveling the playing field.

      If we greatly restrain our AI capabilities in the belief that China will do the same, and then China defects, AI could be so powerful that such a defection could lead to their geopolitical dominance. Therefore any agreement must either have ironclad verifiability, or must be limited enough that defection would not be militarily existential.

      โ€” Dario Amodei

      I am assuming Dario has reasons to believe this, but the models that are actually causing issues right now are all closed weight American models. I'm fairly certain if they were open weight models, we would not have that issue. Why? Because for a start, the economics of serving up these models are only that distorted due to how the big labs can operate. OpenAI is casually burning 18 million USD to brute force a problem on a whim. They are operating subscriptions at a massive loss, distorting the market everywhere. If we had mass accessibility on somewhat equal terms, a lot of the crazy issues we are seeing today would not be taking place.

      A Total Regulatory Failure

      From where I sit, what we observe right now is a total regulatory failure everywhere. In Europe you have some whacky AI regulation that is two years old and completely misses the problems that we actually have and focuses on problems that nobody has. In the US we're seeing a system that is probably best described as turbo capitalism paired with sinophobia and erratic decision-making. In the chaos in which we find ourselves, the reality emerges. And the reality is, even today, really problematic.

      Whatever laws and regulations already exist are largely completely ignored. Plenty of companies are buying data from all over the place that people never agreed could be used for training of AI models. The token economy that is emerging is one that looks like a drug market where you don't know where the requests are going, what model is served up to you, where the GPUs are even running, let alone what you pay for all of this.

      We now have mathematicians who are scared that their use of ChatGPT leads to future models being trained on their ideas, and OpenAI apparently can't even rule it out.

      Ideally the regulators would have forced these models to actually benefit the commons if they are from the commons. The internet has, for instance, greatly benefited from very liberal rulings in the US that permitted scraping. Learning on public data could have been regulated in a way that labs would have to actively support and enable certain forms of distillation. That alone would dramatically change how these models are trained.

      What Might Happen?

      As I said before, I don't think AI is going to usher in an extinction event. In fact, even if nobody were to slow down, I really don't think humanity would have much to worry about. I tend to think it would actually be the large labs that have much more to lose there in reputation and legal responsibilities. I find it preposterous that OpenAI's agents are committing actual crimes out there, but we're just shrugging our shoulders and moving on as if nothing happened. But I'm sure executives in those companies are waking up to the reality that this is not at all popular with a lot of their potential consumers.

      I also think that this entire recursive self-improvement business has a good chance of being a problem. But not necessarily in that it will cause the end of humanity or societies, but that it will just do massive damage everywhere.

      And really, it will just make a lot of the things we are doing much more expensive. Software engineering is an early victim of that. The newfound powers so far have resulted in a new tax that companies need to pay to the model providers, both to keep up with the new speed and to deal with the problem of these machines finding security issues left and right.

      And presumably what is going on in software will happen to more industries. Universities and research groups will have to pour a lot of money into the closed models as well, to keep up with others who do.

      In a way, I'm really confused that society is taking all of this so well.

  3. September 11, 2026
    1. ๐Ÿ”— smol-machines/smolvm smolvm v1.15.0 release

      What's Changed

      • README: the virglrenderer loader path for Nix and NixOS hosts by @NickyHeC in #1224
      • Fix the flake's release hashes and stop the cut from half-bumping nix/smolvm.nix by @NickyHeC in #1225
      • Surface the guest console in a boot failure so the real reason is not lost by @NickyHeC in #1229
      • Make a smaller storage disk work for a Nix install on macOS by @NickyHeC in #1227
      • Report a machine's real memory in status by asking the guest instead of the host by @BinSquare in #1230
      • Let a machine run its own hypervisor by exposing the host's virtualization extensions by @BinSquare in #1231

      Full Changelog : v1.14.6...v1.15.0

    2. ๐Ÿ”— r/Harrogate Never a slow news day around here... rss

      Never a slow news day around here... | I should sent them footage of me emptying by bins during a bit of rain. Quite fancy getting in the news. submitted by /u/LurkishEmpire
      [link] [comments]
      ---|---

    3. ๐Ÿ”— Ampcode News Restack Your Changes rss

      We've added a Restack button that organizes all of your thread's changes into a cleaner set of commits. Use it to split a large diff into logical pieces for review, clean up an agent's intermediate commits before merging, or combine small related commits. The final file contents stay the same.

      Read how to restack and review your changes in the docs.

  4. September 10, 2026
    1. ๐Ÿ”— IDA Plugin Updates IDA Plugin Updates on 2026-09-10 rss

      IDA Plugin Updates on 2026-09-10

      New Releases:

      Activity:

      • disrobe
        • 934c1a95: resolve one php executable in ci
        • 4ffd6ccd: repair recovery regressions and report rendering
        • 5ea61328: correct typed python recovery examples
        • 111de58f: correct reference checks and link the deployed walkthrough
        • 47b299e3: include the pyarmor sample and correct recovery checks
        • 77d1d5af: expand recovery documentation and repair public assets
      • ffxiv_bossmod
      • ida-hcli
        • 4c4c907d: 0.23.0
        • 940984bf: Spell the product name as HCLI in prose text
        • e8b2404b: Skip non-Python executables in get_registered_python_exe
        • 44967cda: Simplify user-facing text for the Python environment commands
        • b7450e3b: Make Homebrew detection and venv plan tests independent of path separโ€ฆ
        • 767a4553: Locate the base interpreter via sys.base_prefix in tests
        • bb305973: Format ke_url_handler.py for current ruff
        • f4c572fe: Add IDA Python environment health check, doctor, and create-environment
      • ida-pro-mcp
        • 5c3525f6: [minor] Expand live session diff coverage
        • fcbbc9e9: [relevant] Raise standalone test timeout
      • idamcp
        • 9ea068dc: Fix race condition between idalib_headless_close and idalib_headless_โ€ฆ
      • Persona4-Decompilation
        • 6af7ca86: Recover battle labels, party panels, and Persona initialization
        • d499934a: Recover model setup, battle collection and field selection
        • 49aff6ab: Recover signed battle callback state word
        • 2e099efd: Recover event, memory-card and battle interface functions
        • cf46d854: Recover byte-exact shuffle card reconciliation
        • 624fdc43: Recover the task-loader parent input contract
        • fe9996f7: Recover material animation loading
        • e29e3319: Recover shuffle, fade, packet dispatch and UI interpolation
        • 69af6a68: Recover four-keyframe orbit camera
        • 4099c2f6: Recover camera keys and party-panel selection
        • d699178b: Recover boot initialization and field rendering with consistent rendeโ€ฆ
    2. ๐Ÿ”— Kagi release notes Sept 10th, 2026 - One login for all of Kagi, and Translate reopens to everyone rss

      One login for every Kagi product

      Kagi now has a single account for all of our products, managed at https://account.kagi.com. This update also adds passkey support , one of our longest-standing requests. #15 @Kai

      What changes for you

      For most people: only the sign-in page. The next time you sign in you'll be taken to account.kagi.com, and your existing email, password, and 2FA continue to work unchanged. Password and 2FA settings are managed there from now on.

      A few cases work differently:

      • Social login (Google, Apple, GitHub, Microsoft): your account will be migrated when we switch over the login page in the coming days. Nothing to do until then.
      • Kids accounts are not migrating and continue to sign in with the passcode received by the account owner.
      • Kagi Mail early testers whose Mail account uses the same email as their Search account: the two are now one account. Sign in with your Kagi Mail password and it works for Search as well.

      Action required if you use 2FA: backup codes were not transferred. Generate new ones at https://account.kagi.com/account/security/recovery after signing in. We'll also email you a reminder in the coming days.

      Suggestions or bugs with the new platform belong on https://kagifeedback.org. If something looks wrong with your account, write to support@kagi.com.

      Kagi Translate

      Kagi Translate is now freemium: every Kagi account gets a monthly allowance, and heavy users can subscribe to a new $8/month Individual plan.

      Existing Starter, Professional, Family, and Team subscribers keep their current access until October 12, 2026. After that date they move to the free tier unless they upgrade to Individual or Kagi Ultimate.

      Read more about the changes โ†’

      Also new in the Translate browser extension:

      • Read aloud (alpha) for selected text, full pages, and "read from here," with a mini player #8787 @liontooth
      • Auto-proofread (alpha) checks text fields as you type #10585 @ttrafford
      • Customizable integration icons: presets, per-integration overrides, and custom CSS #10364 @component5981
      • Orion's built-in page translation now works for everyone, including free and signed-out users #11082 @CielRuby

      Kagi Assistant mobile apps

      When sharing an image or file into the app, you can now start a new thread or share into one of your existing threads.

      Thread retention options, thread sorting, and message reporting are now available in the mobile apps.

      Kagi Maps

      Measure tool is back on mobile

      The measuring tool is available again in the compact mobile controls, with visible drawing lines and measurements. Tapping the map while measuring adds points without opening place details, with the ability to toggle between distance-or-area measurements, (units set in Setting Sidebar)

      Directions and navigation refinements

      Several quality-of-life updates as part of active ongoing improvements to directions and navigation - clearer animations, text, button layout, etc.

      Other improvements and bug fixes

      Kagi Search

      • Added bangs for common built-in lenses: !forums, !fediverse, !programming, !small_web, !academic, and !usenet_archive
      • Search with quotes gives no results #11318 @n4te
      • Show video results without personalization #11317 @mb
      • Having a "Summarize" button is genuinely disappointing #11173 @ctoliver94
      • Feeling Lucky bang does not apply to searches in lenses #9335 @__
      • Search Suggestions: add dedicated "fill suggestion" button for each suggestion item #8159 @artemp84
      • Shield menu doesn't change or disappear when going between images using arrow keys #8940 @Thibaultmol
      • News UI breaks when selecting between time ranges without results #11097 @emptyjar
      • Roman numeral conversion is broken #11415 @tiago
      • Fangraphs fg hashbang has changed #11373 @mergesort
      • Quick Answer still there after disabling "AI" features #11383 @SkyDotBit
      • English queries fail to trigger widgets in non-English UIs #10967 @Hanbyeol

      Kagi Assistant

      Web

      Mobile apps

      • Assistant for Android doesn't search custom assistants #11331 @mb
      • Add find feature to the Android Assistant app #11159 @kslays
      • Voice dictation on Android only outputs the last sentence #11400 @pickx
      • Math equations not working in new Assistant app #11128 @Temanor

      Kagi Translate

      • Read aloud no longer ends short phrases with a stray scream-like noise #11343 @rane
      • Furigana now sits over the whole word instead of just the first kanji #9826 @Astolfo
      • Failed document jobs no longer count against your storage, and documents over the length limit are rejected at upload with a clear message #11359 @ThorwaldWestmaas
      • Right-click translate, define, and proofread now work inside iframes and embedded content #10813 @WorstWizard
      • "Translate with Kagi" is back in YouTube's Subtitles/CC menu #11315 @HealthyAverage
      • Page translation shows an error when it fails instead of a false "translated" checkmark #10602 @Polaris
      • Reddit no longer slows down with the extension enabled #10507 @jarrodldavis
      • Desktops with touchscreens are no longer treated as mobile #10693 @Roon
      • Page translation buttons render correctly in every language #11019 @Hanbyeol
      • Language options show the right names and update once the list loads #9840 @dreifach
      • Overlay popups follow the dark theme, close with the overlay, and stay responsive #11198 @Temanor
    3. ๐Ÿ”— Jessitron When individualism worked rss

      I'm reading more of Hartmut Rosa's narrative of Social Acceleration. Paraphrasing:

      It made sense to have a stable, personal identity when the pace of social change meshed with the change of generations; this is a marker of classical modernity (like, 1800-1970). Before that, and in traditional societies with slower rates of social change, people find themselves defined by pre-existing, enduring structures-an intergenerational identity. After that, in a super- fast-changing society like late modernity (now) pushes us toward a flexible identity, away from continuity. These days,

      [People] must either conceive themselves from the very beginning as open, flexible, and eager to change

      This describes me, and I considered it a virtue. Now I consider it advantageous. A small identity and willingness to shift occupations as the occasion offers, and take pride in new things every few years-useful.

      Rosa goes on to describe the alternative:

      suffering permanent frustration when their projected identities are threatened with failure by a quickly changing environment.

      That describes a lot of America right now!

      Our individualist culture made sense in that ~150 years when we got to have a stable identity that wasn't tied to our ancestry. But modernity is built upon acceleration (of tech; pace of life; and social change), so it didn't stay there. Now the way the world works changes faster than we can grow up, so we have to grow up over and over.

      Right now we're growing into people who use AI for everything. It's jarring! Exciting, and also difficult. Most of us did not ask for this. Most of us would like to be who we are for a few more decades.

      There was a moment when individualism was compatible with human identity formation, a golden age when our lifetime and the pace of social change coincided.

      What to do about it?

      Now I want an identity that stretches longer than a decade. I don't think I can build one for my lifetime, plus that doesn't make sense. Maybe I can weave into other people in the past, future, and now to find a narrative that extends beyond me. If I'm gonna make the world better, it's can be both very local (the people around me) or slower than my lifetime. The day of a great Hero who Changes the World and lives to see itโ€ฆ that moment is gone.

    4. ๐Ÿ”— The Pragmatic Engineer The Pulse: tech companies move to open AI models rss

      Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover Big Tech and startups through the lens of senior engineers and engineering leaders. Today, we cover one out of five topics from last week 's The Pulse issue. Full subscribers received the article below seven days ago. If you 've been forwarded this email, you can subscribe here .

      In May, I covered an emerging trend of companies wanting to cut back their AI spending, starting with engineering departments. Different approaches were being tried:

      • Experimentation with running cheaper, open models on inference providers
      • More investment in model routing to route simpler requests to cheaper models
      • Knowledge-sharing sessions on how to use AI models cost-effectively
      • Setting per-developer monthly AI usage limits

      A few months later, it seems that several companies have managed to achieve this, according to sources I've spoken with.

      Uber: AI costs down 50%

      Uber managed to blow through its annual AI budget in the first three months of this year, and it wasn't a surprise to hear, in May, Uber's COO say that it was getting harder to justify spending on tools like Claude Code without seeing benefits from the leading models. It wasn't long until engineering teams at the ridesharing giant set to work on how to optimize AI spend, and their efforts weren't in vain.

      Uber cut the cost per AI request by 34%, and the cost per AI session by 52%:

      altReducing per-token and per-session spend. Source:Uber

      Of course, Uber keeps using more AI tokens and starting more AI sessions, but thanks to optimizations the cost has been flat since March, despite significantly more usage:

      altUsage up, cost stable Source:Uber

      How did they pull it off at Uber? It was via a combination of different approaches:

      • Open weight models, run using inference: run open weight models on inference services, which are significantly cheaper than frontier ones.
      • Optimized model selection : benchmark all available frontier and open models, to build an accurate picture of their present capabilities
      • Ongoing benchmarking : run benchmarks every week based on real work, and update them
      • Cheaper subagent models : subagents do smaller tasks not requiring the most expensive models
      • Reduce model effort: Uber found that defaulting to Medium effort gives the best cost-to-output ratio with advanced models
      • Optimize requests : trigger automatic compaction above 400K tokens, even for models with 1M context windows
      • Cache prompts : cache prompts to save money when using Uber's own harness, Minions
      • โ€ฆ and more: Uber wrote an engineering blog post detailing the dozens of optimizations taken to reduce token cost without noticeable change in the quality of code generated by agents

      From the outside, the single biggest win seems to be Uber's transition to using open models for certain tasks. Open models cost 2-20x less, compared to frontier ones:

      altThe most expensive open weight model costs $0.30 per code review, vs $0.50 for the cheapest frontier model (and $2.50 for the most expensive one). Source:Uber

      Pinterest makes 90%+ cost savings by dropping frontier models

      Interesting details from Pinterest's earnings call last month reveal how much the social media platform saves by running open models. Here's what CEO William Ready said (emphasis mine):

      "Our approach to model deployment includes our own compact fit-for-purpose models built for Pinterest-specific use cases and suitable open source models post-trained in our own environment within our secure cloud infrastructure. When we leverage open source models, such as with Pinterest Assistant, we are seeing superior performance for our use cases when compared to closed third-party models because we are able to post-train open models on our highly unique data.

      With open models, we are achieving cost per transaction at less than 8% of the cost of comparable closed proprietary models. This gives us substantial headroom to deepen and extend these capabilities over time in a way that is differentiated, highly effective, and cost efficient."

      Basically, what used to cost Pinterest $100 to run on a closed, frontier model, they now spend $8 on by using open models on owned or rented inference!

      AT &T: 56% savings by swapping Claude for open models

      With 100,000 employees, AT&T is a big spender on AI. The telco giant cut its AI bill by 56% while measuring a 2% decrease in the quality of AI's output, after they moved workloads over to open models. From The Information:

      "Austin said he's found that open source models are "just as good or better" than older models sold by the likes of Anthropic and OpenAI. For instance, AT&T's software developers still rely on cutting-edge models for complex tasks like generating code, but can use cheaper open source models for less intense tasks like generating summaries of previously submitted code, he said.

      After the company began using router provider LiteLLM, the costs of some advanced AI tasks such as coding fell by as much as 56% while the quality of the AI's performance fell just 2%, Austin said."

      Anthropic overpriced compared to the rest of the market?

      Only a few months ago, Anthropic was the preferred model (Claude) and harness (Claude Code) among engineers. But Anthropic's models are becoming steeply more expensive at a time when open weight models - and also OpenAI - are getting much cheaper. Meanwhile, Opus 5 is 100x more expensive (!!) than models like GPT-5.6 Luna xhigh and DeepSeek. That may be simply too much to ignore for some tech companies:

      altTypical cost for an AI agent run, per model. Source:Model Zen Garden

      Seeing this data, I'm not surprised that more tech companies are looking to run open weight providers on inference providers, due to the significant savings available from a model that's similarly capable as one from Anthropic.

      What worked for Stripe, Coinbase, Uber & Ramp

      The engineering team at Databricks interviewed engineers at Stripe, Coinbase, Uber, and Ramp, and collected how different approaches helped save costs for them. The summary:

      altSource:Databricks

      To answer the question posed in the header of this report, it's apparent that using open models is indeed the approach offering the biggest savings, followed by smart model routing. Spending controls and context optimization also bear down on costs, but they don't come close to the first two techniques in results.

      A week after publishing this article, Ara Krahzian at Ramp has confirmed that AI spend in August, has, indeed, declined at the top 1% of businesses by 10%, based on Ramp data:

      alt AI spend starting to decline at the top 1% of firms. Source: Ramp

      I 'd wager those companies are not spending fewer tokens, but they are optimizing cost, in ways outlined above.

      Read the full issue of last week 's The Pulse, or check out this week 's The Pulse. This week's issue covers:

      1. New trend of CPU shortages: after a GPU shortage and memory shortage driven by AI companies, we're now experienceding a CPU shortage, thanks to AI agents using a lot more CPU with tool usage. If you will need more compute in the future: secure it now, while you can (even if it's expensive to do so).
      2. Growth dream ends for more COVID-era unicorns: Miro sold itself to Bending Spoons for $1.35B, after it was valued at $17B in 2022. Airtable saw a similar valuation cut last month, and it seems a batch of now-overvalued, VC-funded companies are desperate to sell.
      3. Industry Pulse: Overtime at Google to get Borg working on SpaceX's data centers; SpaceX cuts Claude Code tokens by 90%; OpenAI launches Astra; Meta unveils Muse (and Mark Zuckerberg pushed production code in this release); - to which Mark Zuckerberg made personal contributions; OpenAI's agents go rogue, again.
      4. Do engineers lose touch when AI handles incidents? In the aviation industry, pilots are exposed to emergency situations every six months, to keep their critical problem solving skills sharp. In the tech industry, we might need something similar, especially if AI would take on handling of the simpler incidents.
    5. ๐Ÿ”— Jeremy Fielding (YouTube) Mecanum Wheels Are So Weird They Are Genius rss

      If you want to join my community of makers and Tinkers consider getting a YouTube membership ๐Ÿ‘‰ https://www.youtube.com/@JeremyFieldingSr/join

      If you want to chip in a few bucks to support these projects and teaching videos, please visit my Patreon page or Buy Me a Coffee. ๐Ÿ‘‰ https://www.patreon.com/jeremyfieldingsr ๐Ÿ‘‰ https://www.buymeacoffee.com/jeremyfielding

      Social media, websites, and other channel

      Discord ๐Ÿ‘‰https://discord.gg/F3XuyhNRPc Instagram https://www.instagram.com/jeremy_fielding/?hl=en Twitter ๐Ÿ‘‰https://twitter.com/jeremy_fielding TikTok ๐Ÿ‘‰https://www.tiktok.com/@jeremy_fielding0 LinkedIn ๐Ÿ‘‰https://www.linkedin.com/in/jeremy-fielding-749b55250/ My websites ๐Ÿ‘‰ https://www.jeremyfielding.com ๐Ÿ‘‰https://www.fatherhoodengineered.com My other channel Fatherhood engineered channel ๐Ÿ‘‰ https://www.youtube.com/channel/UC_jX1r7deAcCJ_fTtM9x8ZA

      Notes:

      Technical corrections

      Nothing yet

    6. ๐Ÿ”— r/Harrogate Casual places to get oysters?! rss

      Visiting Harrogate for two nights and my partner is obsessed! We usually find somewhere casual where she can have them while we have a drink as opposed to a restaurant, any recommendations? โ˜บ๏ธ

      submitted by /u/bessj
      [link] [comments]

    7. ๐Ÿ”— Kagi Kagi Translate is back rss

      Kagi Translate is moving to a freemium model and launching a new standalone Individual subscription for $8/month. Anyone with a Kagi account can continue using Translate for free with a limited monthly allowance. For people...

    8. ๐Ÿ”— MetaBrainz Picard 3 Release Candidate 2 rss

      Today the Picard team is making available a second release candidate for Picard 3. We received good feedback on the previous release candidate 1, thanks to everyone for testing and providing feedback. The final 3.0 release is planned to happen in a few weeks.

      Download links and a detailed list of changes since Picard 3 release candidate 1 are available below. For a more detailed overview of what is new in Picard 3 please see the previous blog post Picard 3 Alpha Release.

      While we have all the major features implemented and with the latest bug fixes we are confident in the current code, this is still a pre-release and there might be bugs. If you use this, do so with care, backup your files and please report any issues you encounter.

      If you are updating from Picard 2, note that some of the changes are backward incompatible, hence we recommend you make a backup of your Picard.ini config file before trying this version. You can do so in Picardโ€™s Options under Advanced > Maintenance.

      Whatโ€™s new?

      Bugfixes

      • PICARD-3412 - Picard logs the user out after ~1 hour, requiring re-authentication on nearly every startup
      • PICARD-3413 - Crash in User Interface > Toolbar Actions on Add Action
      • PICARD-3415 - The item views for unclustered and clustered files do not use the system folder icon
      • PICARD-3416 - Generated Appstream appdata file has empty release list
      • PICARD-3417 - Item views and the metadata box do not refresh correctly when interface colors are changed and applied
      • PICARD-3420 - Set proper pygit2 timeouts, reduce the risk of hang
      • PICARD-3421 - Wrong desktop file name passed to QApplication.setDesktopFileName() breaks XDG/Wayland app-id association
      • PICARD-3423 - Snap package does not register the MPRIS2 audio player DBus interface
      • PICARD-3424 - Infinite re-authentication loop when a server rejects a valid OAuth token
      • PICARD-3425 - Submission server is not used for ISRC and rating submission
      • PICARD-3426 - "Submit data to the configured server" checkbox checkmark not visible in dark mode
      • PICARD-3427 - Crash when clicking on a track rating

      Improvements

      • PICARD-3137 - Do not ask for authentication when switching to a server not supporting authentication
      • PICARD-3407 - Add is_from_mb flag to plugin register_script_variable() function
      • PICARD-3408 - Using --debug-opt flag alone doesn't enable debug log level
      • PICARD-3409 - Reduce memory usage
      • PICARD-3410 - Show a busy cursor to acknowledge async lookup and cluster actions
      • PICARD-3414 - Unify boolean environment variable parsing and add PICARD_FORCE_FUSION
      • PICARD-3419 - Add option to standardize artist name only in "artists" and "albumartists" tags
      • PICARD-3422 - Make the "Make It So!" accept button reusable and configurable, and extend it to the Script Editor

      Tasks

      • PICARD-3048 - Document manual editing of tags with metadata view and tag editor
      • PICARD-3215 - Update documentation for restructured CD lookup menu

      Download

      We appreciate your interest in trying this new version. Use with care, backup your files and please use theMetaBrainz community forums and the ticket system to give feedback and report bugs.

      For Windows and macOS you can download the release candidate version from the Picard download page. Linux users can run from source or try the "candidate" channel of the Picard snap package.

      Picard is free software and the source code is available on GitHub.

      Helping out

      We want to provide a polished release of Picard 3.0 that everyone can feel confident to upgrade to. To achieve this, we need the help from the MusicBrainz community.

      The easiest way to help us getting a great Picard 3.0 release is using and testing this release candidate. Please report bugs on the Picard issue tracker and provide feedback in the community forums.

      We also need help with translations, as there are a lot of new features and UI changes over previous Picard versions. We will avoid any further text changes before the final release, so now is the right time to help with translation on Weblate. Please see the translation instructions on the Wiki for details.

      If you are a software developer you are very welcomed to provide fixes and features. Picard is free software and the source code is available on GitHub. See Contributing to Picard on the Picard website to get started.

      You can also look at the new Plugin API and develop plugins for Picard or update your existing Picard 2 plugin to work with Picard 3.

      Acknowledgements

      Code contributions by Bob Swift, Greg Myers, krotka, Laurent Monin and Philipp Wolfer.
      Translations were updated by Marc Riera (Catalan), mfmeulenbelt (Dutch), ninjum (Galician) and st.esser (German).

    9. ๐Ÿ”— smol-machines/smolvm smolvm v1.14.6 release

      What's Changed

      • Bump libkrun and rebuild the bundled libraries for all four platforms by @BinSquare in #1217
      • Show a pack pull's download progress and report the bytes a broken transfer actually moved by @BinSquare in #1218
      • Free a machine's data before the registry write when deleting by @BinSquare in #1219
      • Resolve an archive request against the workspace root by @BinSquare in #1220
      • Bump the workspace to 1.14.6 by @BinSquare in #1221

      Full Changelog : v1.14.5...v1.14.6

    10. ๐Ÿ”— BarutSRB/OmniWM OmniWM v0.6.9 release

      What's New Since 0.6.8

      There are zero breaking changes since 0.6.8.

      • Credit sponsors รlvaro Barchรญn and Marc Hendrichsen.
      • Decompose UI views, overview geometry, CLI completions, and IPC arguments.
      • Decompose IPC models and rule engine and consolidate layout contexts.
      • Fixed scratchpad ownership, persistence, and terminal occlusion.
      • Treat compiler warnings as errors and fix lifecycle bugs.
      • Fixed lifecycle races and streamline Niri navigation.
      • Clean up Swift declarations and concurrency annotations.
      • Reduce settled Niri edge strips and stabilize window parking.
      • Fixed scrolling in the App Rules application picker.
      • Preserve Niri monitor contact through native rounding.

      Official website and documentation: https://omniwm.app
      Installation guide: https://omniwm.app/guides/install/

      Release Integrity

      The OmniWM app is Developer ID signed, Apple-notarized, stapled, and Gatekeeper verified.

      • OmniWM-v0.6.9.zip SHA-256: 9c24ab174e11a1e21155a0640e0323beaa7e22a402e59b69694c8465b002b165
      • GhosttyKit.xcframework-v0.6.9.zip SHA-256: 02ec649259f7465a8e4ae4866f1ef5b9ae876b25190801a340c67052b9324dd4
    11. ๐Ÿ”— HexRaysSA/plugin-repository commits sync repo: +3 releases, -2 releases rss 
      sync repo: +3 releases, -2 releases

## New releases
- [ida-nexus](https://github.com/hexrayssa/ida-nexus): 0.11.0, 0.10.8
- [vtable-context-tools](https://github.com/oxikkk/ida-vtable-tools): 1.2.0

## Changes
- [ida-codemode](https://github.com/hexrayssa/ida-codemode):
  - removed version(s): 0.3.1, 0.3.0
    12. ๐Ÿ”— Console.dev newsletter htmx 4 rss

      Description: Enhance HTML.

      What we like: Simplifies the approach to adding attributes to HTML tags for dynamic features. Now uses fetch(). Makes it easy to implement features like infinite scroll, form post, search as you type, polling, and streaming responses. Still pretty minimal (11kb) and no dependencies.

      What we dislike: Lots of attributes littered all over your HTML, but that is the point.

    13. ๐Ÿ”— Console.dev newsletter Solo rss

      Description: Loader for Linux static binaries.

      What we like: Makes static binaries for GPU-accelerated code actually work. Makes it easy to build self-contained applications that can benefit from acceleration. Compile to musl, but still use common shared packages.

      What we dislike: Incomplete ABI coverage: unsupported glibc calls currently abort. Musl has its own compatibility issues.

    14. ๐Ÿ”— New Music Releases Kings of Leon - My Whole World rss

      Kings of Leon - a new release is available:

      • 2026-09-10: My Whole World (Single)

      Amazon: Canada | Deutschland | France | United Kingdom | United States

      Visit muspy for more information.

    15. ๐Ÿ”— Ampcode News Customize Your Dial rss

      You can now choose the models behind Amp's builtin modes and put your own agents on the Dial. There are two tabs in Settings โ†’ Mode Dial.

      Tune Your Modes

      In Tune Modes, choose the model and reasoning effort for a builtin mode's main agent, Oracle, or subagents. Use it to run those models through your own API key or ChatGPT subscription. The mode keeps its prompt and tools.

      Tune Modes with high selected, the Oracle pinned to GPT-6 Astra, and the main agent and subagents left on Auto

      Connect your key or subscription in Model Routing, then choose models it supports. You can change just the Oracle, or all three roles. Anything left on Auto follows Amp's choices as models improve.

      Billing follows your provider connections.

      Build Your Own Dial

      If you often find yourself using custom agents you built with plugins, like a dedicated code reviewer or a security agent, you can place them on the dial too. Build Dial lets you combine the builtin modes with your agents:

      Build Dial with Medium, High, and the Grok 4.6 plugin mode in three slots, one vacant slot, and a catalog of available modes

      Keep medium and high for building, and add a reviewer with your team's review instructions. A plugin agent can extend a builtin mode, so you only need to describe what it should do differently.

      Drag two to four modes onto the dial, put them in order, and hold to save. Use the mode picker in the app or press Ctrl+S in the CLI to switch between them. Workspace admins can set a shared dial too. Your personal choices take precedence.

      Make the dial yours. The docs cover both tabs.

generated: September 13, 2026 at 13:31:30