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[Other] Uber's $1,500/month AI limit is a useful signal for AI tool pricing <a href="https:&#x2F;&#x2F;www.bloomberg.com&#x2F;news&#x2F;articles&#x2F;2026-06-02&#x2F;uber-caps-usage-of-ai-tools-like-claude-code-to-cut-costs" rel="nofollow">https:&#x2F;&#x2F;www.bloomberg.com&#x2F;news&#x2F;articles&#x2F;2026-06-02&#x2F;uber-caps...</a> (<a href="https:&#x2F;&#x2F;archive.ph&#x2F;ZrwAy" rel="nofollow">https:&#x2F;&#x2F;archive.ph&#x2F;ZrwAy</a>)

[Other] Semantic reification: how to generate UB-free code with arbitrary control flow?

Raytracing Geometries in 3D Rendering

[Other] Recovering Eric Graham's 1987 Amiga Juggler raytracer source code

[Other] Capstone – multi-platform, multi-architecture disassembly framework

[CLI Tool] databow: a Rust CLI to query any database with an ADBC driver

[Other] Branchless Quicksort faster than std:sort and pdqsort with C and C++ API

[CLI Tool] Show HN: Clor – give your agent claws At my last job I spent a year building an agentic coding platform used by hundreds of thousands of people. Along the way I tried building a hosting service on OpenClaw, and also ran Hermes myself for a while. Both projects have some great feature ideas, but when I tried to use them for real work they failed more often than not, and their security models worried me. I just couldn&#x27;t see either one becoming something I&#x27;d trust enough for myself&#x2F;friends&#x2F;family. After a lot of exploration I realized that what I really wanted all along was to create automations using the coding agent I already work in every day. It turned out coding agents were the best tool for automating anything, not just code, as long as they had the right environment and tools to work with.<p>I also spent 20 years leading Linux infrastructure and distributed systems teams. Anyone who&#x27;s written service daemons knows that most of what we think of as &quot;always on&quot; is really just wake up, do some work, and go back to sleep, which is an efficient pattern to use and reason about. Cron has worked this way for decades.<p>So I built Clor, a CLI that lets your coding agent create &quot;claws&quot;, which are background agents that automate anything on a schedule and run on your laptop, Mac mini, or a VM.<p>A claw can be defined and shared as a single CLAW.md file, which contains a bit of metadata (name, schedule, personality, etc.) and one or more ordered tasks. Each task is a real agent run with full tool use, or a plain bash step. Anything you can ask your agent to do once, a claw can do repeatedly. One of my claws tidies my inbox every few minutes, labeling obvious spam, rescuing legit email that got mislabeled, and starring threads I owe a reply to, etc. It&#x27;s way smarter than Gmail&#x27;s filters because it actually reads my mail instead of just matching rules.<p>Installing is the usual command on Linux&#x2F;macOS in the terminal: curl -fsSL <a href="https:&#x2F;&#x2F;clor.com&#x2F;install.sh" rel="nofollow">https:&#x2F;&#x2F;clor.com&#x2F;install.sh</a> | bash. That will set up the CLI, a small scheduling daemon, and a skill that you can run from your agent, &#x2F;claws in Claude Code or $claws in Codex.

[Other] JLink JTAG Access on the Pinecil

[Other] MAI-Code-1-Flash <a href="https:&#x2F;&#x2F;microsoft.ai&#x2F;models&#x2F;mai-code-1-flash&#x2F;" rel="nofollow">https:&#x2F;&#x2F;microsoft.ai&#x2F;models&#x2F;mai-code-1-flash&#x2F;</a><p><a href="https:&#x2F;&#x2F;microsoft.ai&#x2F;pdf&#x2F;MAI-Code-1-Flash-Model-Card.PDF" rel="nofollow">https:&#x2F;&#x2F;microsoft.ai&#x2F;pdf&#x2F;MAI-Code-1-Flash-Model-Card.PDF</a><p>Launching seven new MAI models: <a href="https:&#x2F;&#x2F;microsoft.ai&#x2F;news&#x2F;building-a-hillclimbing-machine-launching-seven-new-mai-models&#x2F;" rel="nofollow">https:&#x2F;&#x2F;microsoft.ai&#x2F;news&#x2F;building-a-hillclimbing-machine-la...</a>

[Other] MAI-Thinking-1 <a href="https:&#x2F;&#x2F;microsoft.ai&#x2F;wp-content&#x2F;uploads&#x2F;2026&#x2F;06&#x2F;main_20260602_2.pdf" rel="nofollow">https:&#x2F;&#x2F;microsoft.ai&#x2F;wp-content&#x2F;uploads&#x2F;2026&#x2F;06&#x2F;main_2026060...</a><p>Launching seven new MAI models: <a href="https:&#x2F;&#x2F;microsoft.ai&#x2F;news&#x2F;building-a-hillclimbing-machine-launching-seven-new-mai-models&#x2F;" rel="nofollow">https:&#x2F;&#x2F;microsoft.ai&#x2F;news&#x2F;building-a-hillclimbing-machine-la...</a>

[Other] GitHub Copilot App

[Monitoring/Observability] Show HN: RePlaya – self-hosted browser session replay with live tailing Hi HN, I&#x27;m one of the founders of s2.dev. RePlaya (<a href="https:&#x2F;&#x2F;github.com&#x2F;s2-streamstore&#x2F;replaya" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;s2-streamstore&#x2F;replaya</a>) is a self-hosted browser session replay tool using rrweb (<a href="https:&#x2F;&#x2F;github.com&#x2F;rrweb-io&#x2F;rrweb" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;rrweb-io&#x2F;rrweb</a>).<p>It occurred to me that a durable stream per session would be a much neater architectural foundation for much of what you&#x27;d want from such a tool. As a unique feature, it also made live tailing straightforward because the player can read from the same stream the recorder is appending to.<p>The alternative architecture is likely an ingest firehose which is then indexed, with associated complexity and latency. You&#x27;d have to string together multiple data systems like a message queue, a metadata database, and blob storage and&#x2F;or an OLAP database.<p>Here the only dependency is S2, which has an open source version you can self-host called s2-lite (<a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=46708055">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=46708055</a>).<p>How it works:<p>- one S2 stream per browser session<p>- large rrweb events (like a full snapshot) get framed across multiple binary S2 records and reassembled on read<p>- active sessions are tailed with an S2 read session, and bridged to the browser over SSE<p>- session listing relies on stream names encoding reverse timestamps, as S2 returns a lexicographic order listing<p>- relying on fencing tokens so a stopped session can&#x27;t be written to again by a late recorder<p>- retention and GC are handled via S2 stream config, so no background job needed<p>Curious to hear from folks on the tool or the stream-per-session model!

[Other] QBE – Compiler Backend – 1.3

[Other] Show HN: I built a way to find and install Claude skills I&#x27;ve been experimenting with ways to increase AI adoption for non-technical people. Basically, all companies are pushing for AI because it&#x27;s all over the news and they feel left behind but most people have no clue where to start. I think 90% of people (ie non coders) are sufficiently well served by using cowork instead of claude code or something similar. If we can get people from sales, customer support, marketing, etc to collaborate with skills and cowork to form a company brain, I think it&#x27;s gold. So I think there&#x27;s opportunity for the community to share skills that work well for 1000s of use cases. However, it&#x27;s currently quite hard to find good skills and figure out if they&#x27;re worth it. Gstack has had immense success because of Gary&#x27;s reach and credibility. Can something like Claudinho.xyz host skills built by the community? What are your thoughts &#x2F; concerns?

[Other] Show HN: MetaBrain – A local document memory for AI agents Hello there HN<p>I experimented with agentic coding recently and I felt the need to track more contextual data by project. Also I felt the need to be able to go beyond the 1D chat to communicate with agents.<p>So I created a local document memory, that is discoverable by agents themselves. The CLI is designed to be easy to pick up by agents. It allows humans to collaborate too by reading &#x2F; searching &#x2F; editing documents in the store.<p>I have a Mac native GUI in the review process, I hope it will show up in the App Store soon.<p>You can try it easily, instructions here: <a href="https:&#x2F;&#x2F;metabrain.eu&#x2F;" rel="nofollow">https:&#x2F;&#x2F;metabrain.eu&#x2F;</a> Here is the GitHub <a href="https:&#x2F;&#x2F;github.com&#x2F;OpenCow42&#x2F;metaBrain" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;OpenCow42&#x2F;metaBrain</a><p>The project is also an experiment for me to build some swift project truly cross platform (Mac &#x2F; Linux &#x2F; Windows) It is open-sourced with the same license as LevelDB that I wrapped in swift to do this project.<p>The agents (and humans) can retrieve content quickly with a search, allowing to re-injecting specific knowledge in a specific context during agentic work. It’s funny, I’ve thought of &quot;inference rule base&quot; as something of a derelict idea of the old functional expert systems. Now that I start working with agents I feel more and more the need to go pick previously working solutions dynamically in such a base.<p>I’d be happy to get feedback. Product fit wise, would this be useful to you or is this just me who is happy with it ?<p>Finally I had fun with the compression of documents, it tries ZSTD quick, if it does not compress the data by more than 10 percent it stores data uncompressed, else it does a ZSTD level 9 compression on the data. I picked up this trick form OpenZFS.<p>Thanks

[Other] Rethinking Search as Code Generation

Show HN: Infinite canvas notes in the non-Euclidean Poincaré disk Hi!<p>This is an infinite canvas note-taking tool where notes are laid out in a non-Euclidean, hyperbolic geometric space. As you drag and navigate through the view, you’ll experience a unique fluid distortion that naturally leverages your brain&#x27;s spatial memory.<p>I’ve been obsessed with the concept of space in HCI for years. Many modern UI patterns are essentially workarounds for the lack of screen real estate. While researching zoom-based UIs a while back, I stumbled upon old HCI papers that used the Poincaré disk model of the hyperbolic plane to organize data. It elegantly projects an infinite space into a finite disk, keeping everything contextually visible.<p>I wanted to build an experimental app around this concept years ago, but the non-Euclidean math was a significant roadblock. Recently, I decided to give it a shot with the help of LLMs. It turns out that LLMs can handle the mathematical heavy lifting quite well, specifically in designing the coordinate systems and optimization algorithms, provided that you guide them with a solid architectural design.<p>This is still an experimental demo, but I hope it leaves an impression. I’d love to know if you find this paradigm practical for organizing your thoughts.

Show HN: Live breath detection and biofeedback from a phone microphone Hi everyone, I am Felix, a famliy doctor from ZH, Switzerland. A couple of month ago I started this little project called shii • haa, a breathing app that uses the phone`s microphone for live biofeedback<p>My prior work in emergency medicine and intensive care was closesly linked to breathing, mostly in critical situations... and let me to reevaluate my own way of breathing. over time one question popped into my mind: can medical knowledge and biofeedback make an app actually promote self-awareness instead of attaching your goals to the award system of the app.<p>it combines signal processing, a breathing state machine and ML. The state machine follows inhale, exhale and transitions in the mic signal. A quality layer rejects noisy or ambiguous windows before signals are used for feedback. All processing is done on-device, no speech or raw audio is uploaded.<p>What I&#x27;m trying to avoid is turning breathing into another score or game. The app gives feedback on rhythm, depth and regularity, but the point is more &quot;notice what you are doing&quot; than &quot;perform well&quot;.<p>I&#x27;d be interested in feedback, especially from people who have worked on signal processing, health UX, or Android&#x2F;iOS audio issues.

[Other] 1-Click GitHub Token Stealing via a VSCode Bug