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AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF generation, batch processing.

The official NGINX Open Source repository.

Agentic AI Infrastructure for magnifying HUMAN capabilities.

Meta Keeps Delaying the Release of Its New AI Model to Developers

Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.

Show HN: My Terminal Waifu made this AI generated song using Suno + Wang Video. enjoy :)

The Smart TV in Your LivingRoom Is a Node in the AIScraping Economy

Pre-Modern Armies for Worldbuilders, Part I: Why They Fight

Show HN: ABC Classic 100 Rankings visualised This weekend is the ABC Classic FM countdown, which prompted me to dust off an old un-published data visualisation of rankings from previous years.<p>I&#x27;ve considered adding a search function, but I also kind of like that it requires a bit of exploration in the current form.<p>Some of the code is a bit clunky and I wouldn&#x27;t mind refactoring it. I&#x27;m also not sure about browser compatibility - I&#x27;ve only got access to a couple of devices to test it on.

The intracies of modern camera lens repair (2024)

[Other] The sandbox agent framework.

Show HN: Omni – Local-first multimodal file search on macOS Finally made something I&#x27;ve always wanted, using the model we built.<p>• SOTA omni embedding model, fully local, indexes text, PDF, image, audio, and video • Swift-native app UI + mlx-swift-transformer core. No Python. • Tested on M3 Pro 18G &#x2F; M3 Ultra 512G &#x2F; M4 Pro 48G. All work fine. • HTTP server exposes search to local agents like OpenClaw &amp; Hermes − Indexing still feels slow even on the latest M3 Ultra, ranging from 10K tps to 300 tps depending on file type − Fans go crazy, high power draw while indexing − Search is near-instant. Multimodal relevance is sometimes arguable, but the idea is recall (the agentic LLM takes the results and refines for the final answer), so maybe that&#x27;s fine

Tribute to Jiro Yamada, Automotive Artist (1960-2025) [video]

Transformers are inherently succinct This paper is being published at ICLR 2026 (top AI conference), and was selected as one of three outstanding papers.

Show HN: On-device transcriber that's 97% accurate at identifying speakers I’ve spent the last seven months building a tool I wish I’d had in my previous roles. MimicScribe is a macOS menu bar app that fits the &quot;AI notetaker&quot; category. It has accurate on-device speaker identification (a first possibly?), real-time meeting talking points for discovery calls, and a fully keyboard- and voice-driven interface.<p>I believe the accuracy of the speaker ID system is its biggest strength. I used fluid audio’s port of (<a href="https:&#x2F;&#x2F;github.com&#x2F;fluidInference&#x2F;FluidAudio" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;fluidInference&#x2F;FluidAudio</a>) Pyannote&#x27;s community-1 as a base. To improve accuracy, the system uses grammar structure cues from the Parakeet STT to mask by sentence. By taking a second set of samples within that mask for cluster assignment, it leverages the fact that most people don’t finish each other&#x27;s… sandwiches in business meetings. It tends to slightly oversegment, as I’ve found it much easier to merge segments or reassign a speaker than it is to untangle an incorrect merge. <a href="https:&#x2F;&#x2F;github.com&#x2F;MimicScribe&#x2F;benchmarks&#x2F;blob&#x2F;main&#x2F;diarization&#x2F;results&#x2F;RESULTS.md" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;MimicScribe&#x2F;benchmarks&#x2F;blob&#x2F;main&#x2F;diarizat...</a><p>The app provides in-meeting talking points using a prompt tuned for discovery type calls. It can suggest probing questions to help you extract more detail or helps you refocus on the big picture with “magic wand” type questions (e.g. “how would your ideal system work”). Getting low latency models to provide novel, relevant, and totally not hallucinated information is a bit of a reach and it tends to restate the transcript frequently but little gems do come from it sometimes so it’s best to think of it as a source of inspiration and be a vigilant gatekeeper.<p>It’s set up so recording can be started and ended via holding a keyboard shortcut instead of connecting to your calendar service. I prefer this for privacy and to keep transcript history from getting cluttered. Tapping the shortcut shows and hides an always-on-top overlay on your active screen regardless of whether you have other apps full-screen or not. Beyond simple navigation, you can also use voice commands to make post-meeting corrections or additions, for instance, you can simply say &quot;merge this speaker with that speaker&quot; to clean up the transcript.<p>It also has push-to-talk&#x2F;dictate functionality with LLM cleanup - what the app started as but that tool was developer catnip, soo many of them.<p>A developer friend who’s worked in finance reviewed the site and said he’d bounce because the privacy story wasn’t strong enough so I added a completely on-device mode and a bring-your-own-key option. Using cloud models does add a lot to the experience, including context aware speaker merging and fragment cleanup, summary items during meetings, action items attributed, etc. On-device mode is completely free and the speaker identification is still very useful.<p>The privacy story is my biggest worry with the app, particularly since its target audience is more technical people. I’d love to get people&#x27;s thoughts on it and any feedback would be super helpful.

Gov.uk has replaced Stripe with Dutch provider Adyen <a href="https:&#x2F;&#x2F;gds.blog.gov.uk&#x2F;2026&#x2F;06&#x2F;02&#x2F;building-for-the-future-making-change-simple-on-gov-uk-pay&#x2F;" rel="nofollow">https:&#x2F;&#x2F;gds.blog.gov.uk&#x2F;2026&#x2F;06&#x2F;02&#x2F;building-for-the-future-m...</a><p><a href="https:&#x2F;&#x2F;www.adyen.com&#x2F;press-and-media&#x2F;adyen-payments-gov-uk" rel="nofollow">https:&#x2F;&#x2F;www.adyen.com&#x2F;press-and-media&#x2F;adyen-payments-gov-uk</a>

Gemma 4 QAT models: Optimizing compression for mobile and laptop efficiency

[Other] pg_durable: Microsoft open sources in-database durable execution

The Quiet Numbers Station: Decoding Nineteen Years of GPS Cryptography <a href="https:&#x2F;&#x2F;lsc-pagepro.mydigitalpublication.com&#x2F;publication&#x2F;?i=865273&amp;p=62&amp;view=issueViewer" rel="nofollow">https:&#x2F;&#x2F;lsc-pagepro.mydigitalpublication.com&#x2F;publication&#x2F;?i=...</a><p>PDF: <a href="https:&#x2F;&#x2F;cdn.coverstand.com&#x2F;61061&#x2F;865273&#x2F;2c88ea662e2b574787232d6b66f1ae8c3cfec2c5.1.pdf" rel="nofollow">https:&#x2F;&#x2F;cdn.coverstand.com&#x2F;61061&#x2F;865273&#x2F;2c88ea662e2b57478723...</a> (article is on page 62)<p>Related: <a href="https:&#x2F;&#x2F;www.404media.co&#x2F;the-u-s-military-quietly-turned-gps-into-a-global-numbers-station-evidence-suggests&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.404media.co&#x2F;the-u-s-military-quietly-turned-gps-...</a>

[CLI Tool] Show HN: Lowfat – pluggable CLI filter that saved 91.8% of my LLM tokens Hi HN,<p>Not sure if anyone would be interested.<p>But, just wanted to share that I&#x27;ve been maintaining my small tool called &#x27;lowfat&#x27; that helps me filters some of my verbose CLI output.<p>It&#x27;s a single binary, works as an agent hook or a shell wrapper. It has a plugin system to customize filters per command.<p>The idea is pretty simple: agents don&#x27;t need the full kubectl get -o yaml or any 10k-line dump to make decisions. So that lowfat sits in between, strips the noise, and passes through what matters.<p>Here&#x27;s my real report after 2 months of personal use:<p>lowfat history --all<p><pre><code> lowfat plugin candidates ───────────────────────────────────────────────────────── # command runs avg raw cost savings source status 1 kubectl get 101x 14.4K 1.5M 93.9% plugin good 2 grep 103x 13.5K 1.4M 96.2% plugin good 3 git diff 81x 995 80.6K 57.9% built-in good 4 kubectl 90x 485 43.6K 33.6% plugin good 5 docker 127x 5.5K 693.6K 96.1% built-in good 6 ls 489x 117 57.3K 56.2% built-in good 7 find 30x 16.5K 495.0K 95.5% plugin good 8 git show 63x 490 30.9K 38.0% built-in good 9 git 177x 368 65.2K 76.1% built-in good 10 git log 86x 556 47.8K 78.5% built-in good 11 kubectl logs 5x 3.6K 17.8K 43.0% plugin good 12 git status 86x 152 13.1K 58.0% built-in good 13 docker ps 20x 467 9.3K 52.8% plugin good 14 kubectl describe 6x 656 3.9K 1.2% plugin weak 15 docker images 9x 940 8.5K 61.8% built-in good 16 k get 2x 2.1K 4.2K 35.9% plugin good 17 terraform 10x 395 3.9K 32.1% plugin good 18 git commit 32x 77 2.5K 0.0% built-in weak 19 docker build 8x 487 3.9K 37.6% built-in good 20 docker compose 22x 979 21.5K 89.4% built-in good total: 4.4M raw → 4.1M saved (91.8%) </code></pre> My toolset above is kind limited, but it works pretty well for my usecase without any interruption Kinda help me not reaching the token limit for my company Bedrock limit usage and keep optimizing the saving on the go for later usage.<p>But, why not alternatives (<a href="https:&#x2F;&#x2F;github.com&#x2F;zdk&#x2F;lowfat#alternatives" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;zdk&#x2F;lowfat#alternatives</a>) ? The answers are: - My goal is to make the core lightweight but extensible via plugins i.e. not trying to bundle every command in the installed binary so that people own their output filters. - Customizable per usecase via plugin or filter pipelines as I am using my own toolset. - Customizable for non-public CLI tools, for example, some enterprise might have their interal CLI tools that public won&#x27;t have access. - People should own their data. So the design is local-first, No telemetry forever. - I kinda love UNIX-style composible pipes, so lowfat-filter has implemented this style. - Be able to adjust aggressiveness of the filter, so we can control that we won&#x27;t strip something the agent needed.<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;zdk&#x2F;lowfat" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;zdk&#x2F;lowfat</a><p>Anyway, if anyone is interested, feedbacks and questions are welcome!<p>Thanks!