Show HN: Shot-scraper video tool for recording YAML-defined webapp feature demos https://ift.tt/5Si3Fsp

Show HN: Shot-scraper video tool for recording YAML-defined webapp feature demos https://ift.tt/kDyf7Ic June 30, 2026 at 10:28PM

Show HN: Fleet – a local-first console for managing Dockerized Hermes AI Agents https://ift.tt/oftlOpU

Show HN: Fleet – a local-first console for managing Dockerized Hermes AI Agents https://ift.tt/PEwmhkK June 30, 2026 at 02:01AM

Show HN: The UNESCO Tsunami Warning Emails Are Gone https://ift.tt/drnACw2

Show HN: The UNESCO Tsunami Warning Emails Are Gone This key piece of tsunami warning and safety was discontinued this morning and evidently there's no way to get it back. :/ https://ift.tt/UbNvXEd June 29, 2026 at 11:36PM

Show HN: Use-zerostack – delegate any task to a lightweight coding agent https://ift.tt/PluCqiK

Show HN: Use-zerostack – delegate any task to a lightweight coding agent https://ift.tt/BerTGPY June 29, 2026 at 01:03AM

Show HN: NanoEuler – GPT-2 scale model in pure C/CUDA from scratch https://ift.tt/HBuk6Yf

Show HN: NanoEuler – GPT-2 scale model in pure C/CUDA from scratch Hi everyone, I started working on nanoeuler after the ban of anthropic's fable because my ambition and dream is to work in the AI field in anthropic. The two interesting reasons that led me to create nanoeuler were (1) interfacing with llm does not mean understanding how they are composed and (2), working on llm with a very low-level layer to understand the correlation between parameters and data and growth of the model and how the GPU works and how some layers can be optimized. So I started working on it with a research aspect by making nanoeuler grow more and more but doing one step after another starting from Shakespeare.txt and understanding what a text generation model understands at 23 million parameters. For example, nanoeuler at that number had understood that Name: started a line and wrote that line with sense. I wrote everything in CUDA because I wanted to not use any intermediary between the model in training and inference and what it had to do. Then the use of SFT and much more, even if in small ways, were really useful to understand the various step to make an llm like a chatbot.Any feedback, help, or suggestions are absolutely welcome! https://ift.tt/aVdXS2O June 29, 2026 at 01:08AM

Show HN: Caliper – pass@k reliability testing for Claude Code and Codex skills https://ift.tt/qgayukA

Show HN: Caliper – pass@k reliability testing for Claude Code and Codex skills Skills for Claude Code and Codex are hard to test. What I mean by hard is that there's no standard way to do it. You evaluate the skill once on something, it looks like it works. You publish it. Then the new super model releases (GLM 5.2 anyone?), it will quietly break for some part, and you won't find out until your users complain. I also faced the same problem, so I tried to build something lightweight to stop doing that. Caliper. It's a local and lightweight harness that runs a skill k times in isolated environments and gives you a pass@k score (How much times it succeeded in these k times). As a non-deterministic technology, you can't just say "it worked once". You need to answer how much it passed in k times. You define success in a YAML spec. I picked YAML to keep a schema and make it still readable for a human. You either use a LLM judge, a Python assertion, or both: Here's an simple evaluation example with a JSON extraction, so you write this in a YAML file: tasks: - name: Extracts action items as clean JSON prompt: "Read /tmp/transcript.txt and write the action items to /tmp/actions.json." expect: "A valid JSON array where every item has owner, task, due. No markdown fences." assert: | import json items = json.load(open("/tmp/actions.json")) assert isinstance(items, list) assert all({"owner","task","due"} <= i.keys() for i in items) Then with the CLI, you'll run it: caliper run extract-actions.eval.yaml --k 5 --baseline What's cool about the --baseline flag is that it will re-runs everything without the skill, so you can see whether the skill is doing the work or the base agent was going to pass anyway: ID Task k(5) pass@k task-1 Extracts action items as JSON 5/5 100% PASS With skill 100% No skill 60% Delta +40% Most models know how to get the JSON right most of the time (JSON extraction was solved by 2 years old already). But that's it, "most of the time" is the bug. That delta shows how the skill actually helped. (It's sometimes 0%, sometimes -100%!) I also created two skills you can get started right away with your favorite harness, e.g. Claude Code, Codex or Pi: - evaluate-skill: run and manage evals without leaving your workflow - grill-skill: reads your SKILL.md, interviews you about what "good" looks like, writes a 3-task spec (happy path, edge case, adversarial), and runs it You can install the skill with the command: npx skills@latest add edonadei/caliper I for now support claude-code, codex, pi, claude-api, openai-api. You can run the agent and the judge as separate backends, so you can run a skill on one and judge with another. GitHub: https://github.com/edonadei/caliper PyPI: https://pypi.org/project/caliper-eval/ Of course, it's a first step. I think the autorater layer can be vastly improved, more handholding to create and iterate on evaluation specs, supporting more harness, why not including this layer into a self-improvement bigger system? If you're also building agentic evaluations, I'm genuinely interested to hear how you are handling that. https://github.com/edonadei/caliper June 28, 2026 at 11:12PM

Show HN: Starglyphs - A constellation puzzle game based on Euler paths https://ift.tt/9jCuPHo

Show HN: Starglyphs - A constellation puzzle game based on Euler paths I am a big Dragon Age fan and sunk hundreds of hours into Inquisition. It had this minigame called astrariums where you had to solve these shapes based on constellation guides by tracing stars. I'm a hobby game dev and wondered if I could procedurally generate these puzzles so they were always solvable. Turns out you can, so I built a space puzzle game around it with a colorful aesthetic. I released it in web form here but I'm currently working on getting it on Steam and mobile. https://starglyphs.com June 28, 2026 at 03:20AM

Show HN: Adrafinil – keep a lid-closed Mac awake only while agents work https://ift.tt/uYUrhoj

Show HN: Adrafinil – keep a lid-closed Mac awake only while agents work A month ago there was a wave of posts and tweets about engineers walking around cafes and parks with their MacBooks propped half-open, as fully closing the lid forces sleep that stops their AI agents. Some people made snarky comments about using tmux or Amphetamine, and some defended their choice with “but I only need it sometimes, and forgetting to disable Amphetamine and finding my laptop discharged in my bag is worse.” This is a solution to this problem. Unlike caffeinate, it will prevent your MacBook from sleeping even with the lid closed, with no external power or display, using pmset disablesleep 1. Unlike other sleep-preventing apps, Adrafinil only activates when there’s an agent actively doing something. It detects agent activity through hooks it installs into Claude Code, Codex, and others. To reassure you it’s working, the app shows the active status in the menu bar, and it plays a chime when you close the lid. Once the agent is done, Adrafinil detects it and lets the laptop go to sleep by setting pmset disablesleep back to 0. It will also let it sleep in case of overheating. And if you want to manually toggle it, you can install an optional MCP and tell your agent to keep the MacBook awake for a specific time. It has four binaries, one of which is a root helper exposing a single setSleepBlocked call. All the logic and policy live in the unprivileged parts. They’re all notarized, and the app is fully open source (MIT). https://ift.tt/6YeD5Em June 28, 2026 at 02:04AM

Show HN: Wind particles on Mapbox from a single EXIF JPEG https://ift.tt/xidvVYu

Show HN: Wind particles on Mapbox from a single EXIF JPEG https://ift.tt/tqXv0HP June 27, 2026 at 11:46PM

Show HN: A Living Neural Web in HTML5 Canvas https://ift.tt/gTivKnV

Show HN: A Living Neural Web in HTML5 Canvas https://techoreon.github.io/verpad/canvas-playground.html June 27, 2026 at 10:05PM

Show HN: TBD, a Mac-native CLI-forward coding agent multiplexer https://ift.tt/2I3TKB7

Show HN: TBD, a Mac-native CLI-forward coding agent multiplexer Inspired by Conductor, dmux, claude-squad, agent-deck, and Git Tower ## What makes it different: (Aside from GUI) A core tenet is -- everything a user can do manually, must be exposed via CLI for agents/automation Best paired with something that lets agents in different worktrees talk to each other (e.g. https://ift.tt/HTjYahr ) ## Background: I used and loved Conductor for months starting around January, but hit some persistent issues that made me realize that a core tool that I'm actively using for most of my waking hours sits too close to my skin to produce itches that I can't scratch myself After realizing I needed to switch to something hackable, I went through a few week-ish long trials of dmux, claude-squad, and agent-deck. They were all great, but I then realized I really didn't want to memorize keyboard shortcuts, and I've managed to put off learning how to drive tmux for over a decade, didn't want to end that streak XD So TBD happened in March. In the months since, it's gotten stable enough to the point where a few former and current colleagues have switched to using it as their daily drivers as well. It's been kind of like a fun little club house we contribute to The architecture is a daemon that handles the bulk of state management and actual work, and CLI and GUI clients as two interfaces. Users go through GUI, LLMs and scripts go through CLI. It works best for Claude Code (our shared daily drivers) but two of us also use Codex on the side, so there's some basic support there as well The only way to run it is to clone and build from source, partially b/c I imagine the main appeal is for people who need to hack on the thing they're using (but also b/c didn't want to shell out for an Apple dev license) I think it's now a good enough starting point for similarly minded folks to use as a base to fork and build your own variants, tailored to your own workflows https://ift.tt/Pmz4Fkp June 26, 2026 at 10:29PM

Show HN: Mantis, A self-hosted LLM gateway https://ift.tt/9uEkyB0

Show HN: Mantis, A self-hosted LLM gateway Hey HNers - Riz here. I got together with a few guys and we built an LLM gateway. It's designed for small teams working on early-stage products, and can be deployed to AWS using a single command (i.e. `mantis deploy`). It's self-hosted, and is designed to belong to you. https://ift.tt/tLYE9eq June 27, 2026 at 12:45AM

Show HN: Puzzle with Strangers. A free multiplayer jigsaw https://ift.tt/es4avwt

Show HN: Puzzle with Strangers. A free multiplayer jigsaw I built this over the last few days. Me and handful of friends are successfully hooked. I recently went to a — for lack of a better word – social/collaborative performance at an art gallery in Berlin where a group of artists filled a huge industrial hall with wooden 10x10cm cubes for people to build structures with. It was beautiful how universal the concept of playing with wooden blocks is and how ephemeral the structures were, people of all ages were put back into a childlike play. The thought about what kind of games need zero explanation stuck with me and i built an anonymous multiplayer jigsaw. We've already spent hours in there and you're invited now as well. Hope you enjoy. https://ift.tt/okCpys9 June 26, 2026 at 10:17PM

Show HN: I created a Scrabble-like word game with simple rules and fun combos https://ift.tt/GayFv3W

Show HN: I created a Scrabble-like word game with simple rules and fun combos When I was in school, my teacher used to play this game to our class. You add one letter turnwise and try to make a word. Later, I tried searching for this game but didn't find the exact match anywhere. The closest was Scrabble, but it was too complicated. So, I decided to build my own. I did make some modifications to make the game more challenging and fun. Back then, we would start with a blank board and also score 2 letter words. Here, the game gets prefilled with random letters so the game becomes more different each time. No scoring for two letter words. The best thing that I added was the combos. If your letter makes 2 or more words, you will get a multiplier for each subsequent word, so the challenge becomes finding a way to score more combos. Initially, I wanted to assign values to each letter like Scrabble, but after running multiple AI-to-AI experiments, I concluded that having flat values per letter increases variances in the game and also reduces the first turn advantage to 0. I still added the weighted game mode if you would like to give that a try as well. And I also added daily puzzles where you get 5 boards, and you need to find the best spot and best letter that scores the most. You can share the Wordle-like result to your friends. You can also play directly on the web at https://ift.tt/1RAp0La or free download in the App Store at https://ift.tt/gPnUha1 https://letterphile.com June 26, 2026 at 03:37AM

Show HN:Every Team Is Building the Same Cache https://ift.tt/zr2pVnw

Show HN:Every Team Is Building the Same Cache https://ift.tt/bOijAHJ June 26, 2026 at 03:10AM

Show HN: Full featured language that compiles to binary https://ift.tt/pKmvXM2

Show HN: Full featured language that compiles to binary Features: 1. Self-hosting compiler 2. C99 backend 3. Built-in dependency injection / IoC 4. Typed business-rule features like decision tables 5. Native binaries + WASM 6. Real app built with it: eXstream https://ift.tt/ERkhTPy June 26, 2026 at 12:45AM

Show HN: OpenKnowledge – open source AI-first alternative to Obsidian/Notion https://ift.tt/IBxm5cE

Show HN: OpenKnowledge – open source AI-first alternative to Obsidian/Notion https://ift.tt/8hStksB June 25, 2026 at 09:34PM

Show HN: Dspyer – self-correcting, optimizable LLM steps for DSPy and LangGraph https://ift.tt/KpYFV74

Show HN: Dspyer – self-correcting, optimizable LLM steps for DSPy and LangGraph https://ift.tt/jwiQgJO June 25, 2026 at 02:38AM

Show HN: LookAway, a Mac break reminder that knows when not to interrupt https://ift.tt/swgeKXU

Show HN: LookAway, a Mac break reminder that knows when not to interrupt Hello, I'm Kushagra and I am the indie developer behind LookAway (I've posted about it earlier but it has received quite a lot of updates since the last time so I am posting it again). LookAway is a native break reminder for macOS that doesn't interrupt. I built it because I work from home and I spend a lot of time in front of my screens. It's very easy for me to get lost in the flow and I can end up sitting for hours. Due to this, I started facing issues like eye strain and back pain by the end of the day. The solution to this was simply taking enough breaks throughout the day. But remembering to take breaks was difficult, especially when I was in the flow. I tried some reminder apps but the problem with those was that they always interrupted me at the worst moments. So I ended up not using them. LookAway is designed not to interrupt. It gives enough heads up before a break so that you're not caught off-guard. It's also context-aware and it automatically pauses when you go into a meeting, start watching a video, record screen, and much more. It even waits for you to finish typing or dictating when a break is due. One thing worth mentioning is the free iOS counterpart LookAway Mirror. When your Mac goes on a break, your iOS devices can also mirror the same break so you don't end up scrolling your phone screen during the Mac break. I've spent a lot of time in making LookAway the least annoying break reminder app and I would love to know your thoughts. It's a native Swift app so it doesn't take much resources (150MB RAM and <1% CPU when idle). It's available to download from the website (lookaway.com), Setapp, and the App Store. Thank you! https://lookaway.com June 24, 2026 at 06:59PM

Show HN: The Cascade Graph – An interactive map of AI and energy constraints https://ift.tt/wJGe0Ed

Show HN: The Cascade Graph – An interactive map of AI and energy constraints Hello, I wanted to share with you all a interactive map of the economics and physics constraints of the AI buildout. It has macro drivers, industrial chokepoints, and where that shows up in markets. I've added 393 nodes and 562 edges to capture other supply / physics constraints as well. There's no sign up, and no pay wall, it's all free. Please let me know what you think! https://ift.tt/4CfYr19 June 23, 2026 at 08:52PM

Show HN: Wordit – Change One Letter, Keep the Chain Going https://ift.tt/hu9sB16

Show HN: Wordit – Change One Letter, Keep the Chain Going Hi everyone, I got this idea for a game where, starting from a four letter word you need to go as deep as you can in your vocabulary, changing only one letter per word. bear -> beer -> peer... Each correct word gives you 1 point Each incorrect word takes one life away from you, you start with 3 https://ift.tt/0qdxLFf June 24, 2026 at 12:27AM

Show HN: I scanned every YC Spring 2026 startup for what AI crawlers see https://ift.tt/XPyvnFL

Show HN: I scanned every YC Spring 2026 startup for what AI crawlers see Used 'potatometer.com' to scan and analyze all All 197 YC Spring 2026 startups on their SEO / GEO / AEO technical setup. I scanned the URL each startup lists in YC's directory. Most are readable by AI crawlers. Most don't tell a crawler what they are. Read more in the blog above. https://ift.tt/U5lhE0q June 23, 2026 at 08:10AM

Show HN: Durable Agent Sessions API (Preview) https://ift.tt/HhVZfFd

Show HN: Durable Agent Sessions API (Preview) https://ift.tt/0hdVuFL June 23, 2026 at 07:07AM

Show HN: Kitcat 2.0 – A Matplotlib back end for terminal plotting https://ift.tt/873ML5y

Show HN: Kitcat 2.0 – A Matplotlib back end for terminal plotting https://ift.tt/OWo1wsm June 22, 2026 at 11:00PM

Show HN: Pure Effect – Reproduce production bugs on your laptop without a DB https://ift.tt/R3IV6Mz

Show HN: Pure Effect – Reproduce production bugs on your laptop without a DB Hi HN, I think it's safe to say that the majority of developers don't give a second thought to writing code with I/O tangled in business logic. It's all too common to see code like: const user = findUser(email); if (!user) await saveUser(user); Now, you may ask: what's the big deal? When we write code like this, two things happen: 1. It gets harder to debug production bugs. Unless you have the exact same database and remote API services to connect to, you may fail to reproduce the bug. 2. You have to use mocks and fakes in your tests, or use test containers, which only help somewhat, and they are slow! To solve these issues, I built Pure Effect, a tiny TypeScript/JavaScript effect library. The core idea is simple: if a function performs I/O, it isn't pure. But if it returns a description of the I/O it wants to perform, it is. So instead of await findUser(email), you return a Command object that says, "I would like to call this function, and when it finishes, here's what to do next." Your business logic becomes a pure function. Same input, same output, every time. The database never gets touched until the interpreter (runEffect) runs. When I first started the library, I didn't expect just how far that one idea would stretch. Once your pipelines are just data, a lot of wonderful things become possible: - No need for mocking libraries. You walk the tree in tests and assert on its structure: assert.equal(flow.cmd.name, 'cmdFindUser'). Nothing is executed. - Wrap any effect with Retry(effect, { attempts: 3, delay: 200, backoff: 2 }). The configuration is plain data, so you can assert on it in tests. - Every command's input and output flows through the interpreter, so you get a full execution trace for free. You can write a simple timeTravel() function that replays it locally without touching any I/O. Perfect for debugging complex production bugs. - An onBeforeCommand hook sits between your business logic and the interpreter. Since it sees every intended side effect before it fires, it can be used to enforce runtime guardrails. You can quarantine destructive calls before they happen for example. - You can review AI-generated code before it runs. Since Pure Effect pipelines are plain data, you can inspect what the generated code intends to do before it touches anything. There are just six primitives: Success, Failure, Command, Ask, Retry, and Parallel, plus effectPipe and runEffect. Zero dependencies. Under 1 KB minified and gzipped. How it compares to Effect-TS Effect-TS is the full-featured option in this space and has a large ecosystem. Pure Effect offers a different tradeoff. It covers the 80% case: testable pipelines, dependency injection, retry, and OpenTelemetry hooks, all in under 1 KB with zero dependencies and no new vocabulary to learn. Effect-TS is a framework you build around. Pure Effect, on the other hand, is a pattern you drop into existing code. I've been using Pure Effect in production since December. It's at v0.8.0, not 1.0 yet, but stable enough that I wanted to put it out there and hear what people think. GitHub: https://ift.tt/9zJMtsD I wrote five posts that document how Pure Effect evolved. They are tagged at https://ift.tt/YUyn48K if you want the longer story. https://pure-effect.org June 21, 2026 at 11:06PM

Show HN: DebugBrief – turn debugging sessions into reports, no AI https://ift.tt/jkSQhn8

Show HN: DebugBrief – turn debugging sessions into reports, no AI https://ift.tt/QFh1C0x June 22, 2026 at 01:27AM

Show HN: CleverCrow: give tokens to your favorite projects https://ift.tt/9K2XU3a

Show HN: CleverCrow: give tokens to your favorite projects Howdy all. I'm Zack :wave:. I've been thinking about the problem of misguided AI pull requests and figured I'd throw a possible solution out there for feedback. Basically, CleverCrow lets supporters give tokens to a GitHub repo (or set of issues in that repo) for the maintainers to use to build/fix stuff. The fun implementation challenges have been around implementing the pooling dynamics and keeping the maintainers in charge while the backers are motivated to support their work. https://clevercrow.io June 22, 2026 at 12:36AM

Show HN: We post-trained a model that pen tests instead of refusing https://ift.tt/W4x1YnM

Show HN: We post-trained a model that pen tests instead of refusing Anthropic and OpenAI's publicly available models are explicitly guard-railed so that they refuse offensive tasks. And their cyber-focussed models are gated for enterprises. This leaves SMEs and mid market open to major vulnerabilities. AI can be used as both an adversarial and defensive tool in the world of cyber. A worst case outcome is if only the adversaries have access. Meanwhile, most existing AI cyber tools are just wrappers. The problem is that they still have all the guardrails on from the foundation model where they will inherit its refusals. For this project we've post-trained a specific model on a decade of capture-the-flag contests. This won't be made available to anyone and everyone, but we do believe that responsible SMEs and midmarket companies also need access to these tools in order to identify key vulnerabilities in their systems; not just enterprises. We have developed two modes that run over a CLI: • Security scan: a read-only audit of your local codebase for vulnerabilities. It only reports what it can tie to a specific file and line, so you're not wading through vibes-based findings. • Pen test: an active adversarial mode that will try to break a live system in a sandboxed environment. It proves each vulnerability by running the exploit and showing the request it sent and the response your code gave back, not a confidence score. Currently gated. To show what the scan does, we pointed it at Bank of Anthos and it found an integer overflow in the transfer path: amount is an int, and amount + fee can overflow negative, so the balance check passes and you move funds you don't have. Plus the usual auth and secrets issues. (Bank of Anthos is Google's open-source bank. It's a known app and some of it is intentionally weak, which is the point: you can clone it and re-run the scan yourself instead of trusting a screenshot) The base model is a Kimi K2.6 (open weights). We didn't pretrain from scratch. We post-trained it ourselves, SFT on CTF writeups, then RL with verifiable rewards against actual exploit checks. How the harness works: Along with the model we built the harness to support this. The harness runs on a multi-agent swarm: an orchestrator splits the job across subagents running in parallel, each owning a slice, then synthesising one report. The CLI is a local binary (brew/curl). It reads your code locally, then sends context to our inference API over TLS tcpdump it and you'll see exactly what leaves and where. Install is free; and you can run a scan for free up to 2m tokens, then need to pay for tokens beyond this. For full disclosure this is a product part of Cosine (YC W23) Up for debate: tool safety, e.g. domain verification is one method that proves control but not necessarily permission. How would you gate a pen-test tool given that? https://ift.tt/MbV9LWz June 20, 2026 at 07:19PM

Show HN: Continuous Nvidia CUDA PC Sampling Profiler https://ift.tt/R1rlsmk

Show HN: Continuous Nvidia CUDA PC Sampling Profiler Blog post about how we extended our open source profiler to include support for continuous production PC sampling. https://ift.tt/GyJPTSd June 15, 2026 at 09:19PM

Show HN: PostgreSQL MCP Server with 135 tools for various purpose https://ift.tt/AUzZ3qo

Show HN: PostgreSQL MCP Server with 135 tools for various purpose https://ift.tt/OaSVRgo June 20, 2026 at 12:42AM

Show HN: NanoEuler – GPT-2 scale model in pure C/CUDA from scratch https://ift.tt/qpd4VQU

Show HN: NanoEuler – GPT-2 scale model in pure C/CUDA from scratch https://ift.tt/K1cvMG0 June 19, 2026 at 11:48PM

Show HN: I built a daily flag quiz in honor of the World Cup https://ift.tt/IGNAcYy

Show HN: I built a daily flag quiz in honor of the World Cup https://orbisearth.web.app/ June 19, 2026 at 01:45AM

Show HN: Run Agent Skills with mistral.rs v0.8.10: /v1/skills support and more https://ift.tt/OFbKrzN

Show HN: Run Agent Skills with mistral.rs v0.8.10: /v1/skills support and more Hey all! I'm the maintainer of mistral.rs. I just landed support for OpenAI-compatible Agent Skills via a /v1/skills endpoint, and it works with local open models. Until now Skills have basically been locked to closed models, and with the ability to have private, local intelligence becoming increasingly important, but this feature allows you to do XYZ with local models. It's fully compatible with OpenAI's /v1/skills API, so you can drop mistral.rs into your existing code with minimal difficulty. We support the accompanying tools too: /v1/files or input_file for attaching files to your prompts, and mistral.rs also allows models to send generated files back using the OpenAI-compatible method. It's also easier than ever to try mistral.rs: we are including prebuilt binaries for NVIDIA CUDA, Apple Silicon, and CPU! # Linux/Mac > curl --proto '=https' --tlsv1.2 -sSf https://ift.tt/L2OIdhJ... | sh # Windows > irm https://ift.tt/L2OIdhJ... | iex Then: mistralrs serve --agent --isq 4 -m google/gemma-4-E4B-it Super excited for you to try this out and any feedback! Do you have any suggestions for what you would like to see in the next releases? Check out the GitHub: https://ift.tt/choOgPQ Docs & Quickstart: https://ericlbuehler.github.io/mistral.rs/ June 18, 2026 at 12:33PM

Show HN: NGB, an open-source .NET platform for document-driven business apps https://ift.tt/wOAsXtz

Show HN: NGB, an open-source .NET platform for document-driven business apps https://ift.tt/hoYmpEy June 18, 2026 at 11:20PM

Show HN: Reyn – local-first AI that journals and recalls your work https://ift.tt/8T1CW4Z

Show HN: Reyn – local-first AI that journals and recalls your work Hey HN, I built Reyn - which I like to describe as "granola but for everything". You're probably thinking another screen capture AI tool (which is true). Same as always, the biggest question that comes up is privacy, so I'll talk about that first 1. raw screen data is never stored in the cloud 2. user controlled filters are granular to the point that you're able to configure specific apps, windows, websites, or even keywords to be discarded immediately (once again never leaving your mac) and never captured down the pipeline I personally built it because I find it useful and always had the problem of organizing my day (not note taking or task management), as well as sharing context on things that just happened to go undocumented throughout my day. As I was building it I decided to go even further and see if I could collect useful insights and find room for improvements in my day to day workflow. This led to the current version of Reyn and its differentiating factor being the fact that it has a proactive layer. Most tools in this space are reactive - you ask, they retrieve. Reyn surfaces insights on its own and sends a daily recap of what you worked on, what's still open, and what deserves attention. The journal feature also lets you search across basically anything you've done on your Mac. The proactive insights work by first having you configure what your ideal workday looks like — whether that's hours worked or the type of work being done. We have a few broad categories that tasks fall under, with more customization coming. Current integrations: Obsidian (available now, improvements in progress) Gmail, calendar, web search via a floating window with some agentic functionality Notion (coming soon) BYOK for LLM API requests (on the roadmap) ... and more It's still early, but the journal and insights features are the strongest parts right now. Would love some feedback especially on the privacy model. My personal take - I think with enough safeguards in place, the data aggregated about your work is fully in your control. A lot of these data sources already store your data. If you're using Notion, Claude, or just browsing a website, that data is already being stored somewhere. Reyn is just aggregating it and putting it to work for you. Happy to answer any questions about how it works usereyn.com (public beta) https://ift.tt/0nSvKg7 June 18, 2026 at 04:01AM

Show HN: Vpod – Tiny Linux sandbox running in WASM https://ift.tt/uXc7zsa

Show HN: Vpod – Tiny Linux sandbox running in WASM Hi HN, I spent the last few months reading the RISC‑V specification to build the lightest possible sandboxes. The idea behind a vpod is to quickly spin up a Linux sandbox from snapshots (Alpine by default) without any setup or subsystem required. The trade-off for portability and security is raw CPU speed. So we don't expect it to match native workloads with Python or pip, for example. More info is in the README https://ift.tt/YygiS9H Happy to answer any questions! https://ift.tt/YygiS9H June 17, 2026 at 10:11PM

Show HN: Sabela – A Reactive Notebook for Haskell https://ift.tt/J0S1c8N

Show HN: Sabela – A Reactive Notebook for Haskell Sabela is a reactive notebook for Haskell. The name is the Ndebele word for "to respond." Cells respond to each other on change. Initially it was meant as a tool for working with data but it has turned out to have a lot of pedagogical value outside of data analysis work. There is a gallery to read through on the website and a number of examples in the repo showcasing things like: * Python interop * Widgets and animation * Exploratory data analysis If you find any of this interesting please try it out. Any feedback is welcome. https://ift.tt/6QnF0UZ June 14, 2026 at 02:03PM

Show HN: Ctx, save tokens by loading only the relevant tools https://ift.tt/9Wcobtv

Show HN: Ctx, save tokens by loading only the relevant tools Hi HN! Token cost has started to become a high topic of concern to all of us. I tried a few (awesome) tools such as rtk, caveman, and the recent (hillarious but effective) ponytail. What they usually do, is in-line token reduction, e.g. try to compress requests / responses as much as possible. But then it hit me (and I’m sure others had similar ideas) - just like we have routers that pick the right model, why not have something that will also narrow down the amount of available tools, skills and mcps based on repo/context? People usually accumulate skills, agents, MCP servers, harnesses, prompts, repo instructions, and local scripts. I’m not saying we are all hoarders, but we sort of are. When did you remove a skill recently? After a while, the model has way too many options to choose from. ctx tries to fix that by selecting context before the session gets bloated.So no, it doesn’t cleanup your messy garage, but it gives you magic glasses that let you focus only on the tools you need. It does it by watching the repo and task, walks a graph of available tooling, and recommends a small top-scored bundle of skills, agents, MCP servers, and harnesses. How does it know? To make sure results are not hallucinated, and repeatable, I curated a list of 91k+ skills, 467 agents, 10.7k MCP servers, 207 harnesses, and built a graph to help ctx make decisions on what to recommend. While I used AI to generate it of course, I curated it and revised it to make sure the data is up to date. So how this is different from rtk, caveman, ponytail, and similar token-saving tools? As mentioned above those tools mostly reduce tokens after something is already being used. rtk compresses command output. caveman-style tools make the assistant respond with fewer words. ponytail, is, well, awesome, but again it focuses more on reducing code (YAGNI) ctx is upstream. It tries to avoid loading irrelevant skills, agents, MCPs, and harnesses into context at all. So it is not really a replacement. It should work side by side with them! Use ctx to choose the right tools. Use rtk to reduce terminal-output noise. Use terse-output tools if you want shorter responses. The goal is simple: save tokens without forcing the user to manually test and compare thousands of possible skills, agents, MCP servers, and harnesses. Repo: https://ift.tt/zjWi0xF https://ift.tt/zjWi0xF June 16, 2026 at 11:44PM

Show HN: StarScope – Free astronomy dashboard for observers outside the US/UK https://ift.tt/Xpmth4l

Show HN: StarScope – Free astronomy dashboard for observers outside the US/UK https://starscope.live/feed June 16, 2026 at 12:51AM

Show HN: Understand and reduce token usage with ContextSpy context profiler https://ift.tt/Tkxo9Pn

Show HN: Understand and reduce token usage with ContextSpy context profiler https://ift.tt/Qk5ExfP June 16, 2026 at 12:59AM

Show HN: A pure-Ruby X11 terminal https://ift.tt/QURWcHO

Show HN: A pure-Ruby X11 terminal I use this as my regular xterm replacement... Why? Because I can. It's pure-Ruby down to the font-renderer, and the X11-bindings. (I also run a Ruby WM, a Ruby editor, file manager, and more, so this is just par for the course of my descent into madness) It supports double-width and double-height text, unicode (but double-width characters may currently be rescaled down), layering fonts, special rendering of box-drawing characters (to ensure they seamlessly scale and connect, and has reasonably complete vt-100/vt-102 emulation. The whole thing is available as a Rubygem and comes with an ANSI text backend, so you can run your terminal in your terminal. The bulk was written manually, but the last few days I had Claude write a test harness to shake out a bunch of bugs, and start refactoring and cleaning up the code base (it's still full of warts). https://ift.tt/EiGAcSP June 15, 2026 at 11:45PM

Show HN: Solaris the Thinking Ocean Simulator https://ift.tt/hRDxMIN

Show HN: Solaris the Thinking Ocean Simulator https://ift.tt/sa3XIQg June 15, 2026 at 02:47AM

Show HN: Trace – Offline Mac meeting transcripts you can flag mid-call https://ift.tt/hBWCkLn

Show HN: Trace – Offline Mac meeting transcripts you can flag mid-call I'm the developer of Trace, a non-intrusive, shortcut-driven Mac app that records and transcribes your meetings on-device. I know, another meeting transcription app. Please bear with me though, I'm confident that this is at least a little novel. I primarily built Trace for myself. I'd been using MacWhisper, but there was enough fiddling before each call that I'd forget to start it and walk out of an hour-long meeting with nothing written down. So the things I cared about most were that it's quick to activate and stays out of the way. You activate Trace by pressing a global shortcut (configurable), which reveals a small bar at the bottom of your screen (there's also a keystroke and/or option to hide it entirely if you'd rather not see it at all). As I was building it I wanted to bake in a couple of workflows I'd wished for in other transcription apps. 1. Mid-meeting you can press another global shortcut to mark a "key moment" and type a note. The note shows up in the resulting transcript inline at that timestamp. I wanted to add this because I kept catching myself thinking "wait, that bit matters" in meetings and reaching to jot it down in a separate app like Obsidian, which I then needed to add context to, which took me out of the meeting. I use it all the time. If I paste the transcript into an LLM afterwards (which I find myself doing more and more these days) the important moments are flagged so it doesn't gloss over them. This is more noticeable in longer meetings with lots of topics. 2. With another keyboard shortcut you can summon a rough live recap (subtitles, basically) to quickly recap what's just been said. Trace uses standard macOS microphone and system recording APIs to capture both sides of the conversation as two separate tracks and then runs the system side through on-device diarization to identify speakers. Right now we only label them as "Speaker 1", "Speaker 2", etc but there are plans for speaker labelling in the future. You can also show a "live recap" as the call is happening to review what someone just said. All transcription models run on your machine. To be clear though, Trace doesn't do any of the summarising itself, it just produces a markdown transcript, so if you want summaries then you need to pass the output to an AI. The app is sandboxed and your audio/transcripts are never uploaded anywhere - they just exist as audio files and markdown on disk. The only network call Trace is required to make is on the first run to download the speech and speaker models (around 500MB) from Hugging Face, and after that it can be used fully offline. If enabled, a Google Calendar integration can auto-name sessions but that needs a network connection. The app is £9.99 on the macOS App Store. I've been using it every day for months now and I'm super happy with how it's improved my workflow. Feedback very welcome. https://traceapp.info June 14, 2026 at 02:11AM

Show HN: Philosophy for Kids https://ift.tt/VLfw7X9

Show HN: Philosophy for Kids Sometimes my son asks me 'why' questions that could be answered well by a kid-friendly philosophy article. But I don't know where to find those, so I ask Claude or ChatGPT, and have a specific workflow for getting the type of output I want. I figured other people might find those AI-generated articles helpful, so I put them here: https://ift.tt/ENz5J17 There's a search box at the top. https://ift.tt/ENz5J17 June 14, 2026 at 11:45PM

Show HN: Slopsome – a VRAM fit calculator and tok/s database for local LLMs https://ift.tt/LD9XYTk

Show HN: Slopsome – a VRAM fit calculator and tok/s database for local LLMs https://slopsome.com June 14, 2026 at 01:14AM

Show HN: Galdor – a Go LLM agent framework with built-in tracing and replay https://ift.tt/QrVPWmE

Show HN: Galdor – a Go LLM agent framework with built-in tracing and replay https://ift.tt/QGUDtoC June 14, 2026 at 12:34AM

Show HN: Turn your name into a tree in an infinite procedural shanshui landscape https://ift.tt/INP1tnb

Show HN: Turn your name into a tree in an infinite procedural shanshui landscape Hi HN! I made this after collecting hundreds of "name → tree" submissions at ITP. Live: https://ift.tt/Lp4ywkJ Source: https://ift.tt/yUf96kL Plant a tree: https://ift.tt/yTQ7r3N Pan and zoom an infinite procedural landscape. Each name is converted to ASCII codes, which grow into a unique tree (breadth-first branching; repeated digits become mathematical roses). Mountains use midpoint displacement + Perlin noise, with SVG radial gradients in the blue/green/gold palette from Wang Ximeng's "A Thousand Li of Rivers and Mountains." Inspired by Lingdong Huang's {Shan, Shui}* ( https://ift.tt/aiAVvMW ). Every tree is someone's name, signed with an APack stamp ( https://ift.tt/BvT8q9a ). Try planting your name, then pan along the ridgeline to find it. "My trees" lets you jump back to ones you planted. Happy to answer questions about the terrain algo, name→tree encoding, or the Riso print we tiled at ITP Winter Show! https://ift.tt/Lp4ywkJ June 10, 2026 at 08:09PM

Show HN: Nenya – A lightweight, highly secure AI API Gateway/Proxy written in Go https://ift.tt/XrDhYeH

Show HN: Nenya – A lightweight, highly secure AI API Gateway/Proxy written in Go https://ift.tt/dvsLHa6 June 12, 2026 at 11:02PM

Show HN: Vilvona AI – Self-Hosted AI Assistant with Tamil and Hindi UI https://ift.tt/cL1v2Nk

Show HN: Vilvona AI – Self-Hosted AI Assistant with Tamil and Hindi UI https://ift.tt/LwmgyB1 June 12, 2026 at 11:56PM

Show HN: Nuts – pip/NPM for Java with first-class workspaces, JDK provisioning https://ift.tt/Xl7kdOb

Show HN: Nuts – pip/NPM for Java with first-class workspaces, JDK provisioning My frustration with distributing java apps didnt show up recently. I remember having implemented my first network jar downloaded back in the 2000's because i needed applet like feature support with desktop full control. Years after, the problem is the very same. Webstart didnt really took off and the only mean i had in my projects was the ugly fatjars, including the (for me) uglier spring-boot repackaging that changes the application classloading behaviour and hence giving me by time some headackes i was not prepared for. So basically nuts started as a response to this frustration 9 years ago, but from now i think its mature enough (used in production) to be shared, and forecebly i am more keen to need suggestions and help from fellow contributors. https://ift.tt/gsJDKEL June 11, 2026 at 03:53AM

Show HN: AVP – an agent can't leak a secret it never had https://ift.tt/f70qDpY

Show HN: AVP – an agent can't leak a secret it never had A process can't leak a secret it never had. Shai-hulud, prompt-injection - you name it. They cannot steal what your agent (or an process) don't have. I run coding agents (Claude Code, Codex) on my own machines most of the day. Every one of them wants real API keys in env and I was scratching my head for the last few months how to contain it. The usual answer to this is a firewall. I don't buy it. A firewall tries to contain a secret the process is still holding, and the rules are painful to maintain. AVP gives the agent a placeholder and injects the real value at the last moment, on the wire: ``` # the agent's env holds only a placeholder STRIPE_API_KEY=avp-placeholder # agent sends: Authorization: Bearer avp-placeholder # AVP forwards upstream: Authorization: Bearer sk_live_...real... ``` Keep your passwords in your vault where they belong. AVP initially relies on Bitwarden as a secret manager. It's MIT licensed. Appreciate any feedback. https://ift.tt/V5yC7rZ June 12, 2026 at 12:40AM

Show HN: Stillwind – High Resolution Electronic Component Search https://ift.tt/KqO2N3h

Show HN: Stillwind – High Resolution Electronic Component Search We’ve spent the last couple of months building Stillwind Search, a search engine for electronic components that helps users find parts that fit even the most complex set of specifications. After talking to the people that actually build PCBs we found out that finding the exact part you are looking for, is consuming enormous amounts of times, is very tedious and then often doesn’t yield the best results. So we tried to cut down this search time by just requiring a (broad) description of the specifications and we find the correct part in minutes, not hours. This is possible through our own database of parts and their properties. We used LLMs to extract every parameter about a part into >1k schemas, collectively covering more than 130k properties. This depth of properties could no longer be visualized, so the database is queried interactively by an AI agent (Sonnet 4.6) to find the needle in the haystack of parts. Before results are shown, we use another model to verify the data (that’s why it might take a moment before the first results appear). We currently have almost all microcontrollers, sensors, and other advanced ICs on the market, as well as a wide selection of passives and generic parts. We are working on adding more parts and are more than happy to take suggestions. I know that folks on HN like technical details on how this works, so let me give a short overview: Frontend: SvelteKit + Cloudflare Workers + Hyperdrive Backend: PostgreSQL 18 (with io_uring) database, with extensions on NVMe drives hosted on a beefy server. We appreciate all feedback and are happy to answer any questions :) Btw: We are already working on a way that you can search combinations of parts, finding the optimal combination of parts. https://stillwind.ai June 11, 2026 at 11:42PM

Show HN: Atlasphere – Live Infrastructure Diagrams https://ift.tt/dMeon5I

Show HN: Atlasphere – Live Infrastructure Diagrams Hi HN. My name is Andrey. On a regular business day, I'm a software engineer working at AWS. Outside of work hours, I spend time on my hobby - writing code. I was once building a pet project that allowed customers to spin up fully synchronized blockchain nodes within just a few minutes. The backend was split into a control plane and a data plane, each with its own AWS account. Later I added two more AWS accounts. One for shared RPC nodes. One for the Analytics Service. Since I love to visualize things, I used drawio to visualize the architecture. With time, I noticed a pattern. I'd write some code, add a few lambda functions, update my drawio diagram, write more code, introduce a few more resources, test things, see that everything works fine and go to sleep with a smile on my face. Next week I'd check my diagram, and shockingly, it's missing some of the resources! This kept happening for a few more weeks until I decided to fully abandon the project until my infrastructure diagrams could stay in sync with my cloud account. That's how Atlasphere.io was born. I've been working on it for the past 6 months and I think the product is ready for some feedback :) A few notes: - Atlasphere uses a ReadOnly IAM role to scan your AWS account (my account reaches your account through a trust relationship). - The number of services is currently limited (WIP) - It's a macOS app - It's NOT an Electron app, i use Rust + Webview What am I looking for? All I really need is for someone to try the app and tell me what they like about it and what they absolutely hate about it, haha! The website is https://atlasphere.io/ June 9, 2026 at 06:05PM

Show HN: Meadow Mind – a 7B diffusion LLM plays Gym games with zero training https://ift.tt/lCaVpw4

Show HN: Meadow Mind – a 7B diffusion LLM plays Gym games with zero training https://ift.tt/ZeW91Mi June 10, 2026 at 11:11PM

Show HN: Extend UI – open-source UI kit for modern document apps https://ift.tt/OmQyagr

Show HN: Extend UI – open-source UI kit for modern document apps We're open-sourcing 14 components & examples today for PDF, DOCX, and XLSX viewers, plus bounding box citations, file upload, e-signature, and more. It's MIT licensed and fully customizable. Demo video here: https://ift.tt/WH6skeN When we started, we tried every file viewer and document component library we could find. Unfortunately, none of them had all the functionality (and polish) that we wanted, so we ended up building our own for https://extend.ai/ . It was only ever meant to be internal, but enough customers kept asking for it that we decided to open source it. It's useful for building document processing agents, real-time user facing document intake flows, or all kinds of internal tooling. We naively thought this would be a solved problem. Turns out, making PDF/XLSX/DOCX viewers that work at scale is not trivial...we use and maintain it for Extend ourselves, so we've fixed a lot of edge cases that came up while running millions of pages / day through our own system. Our hope is that with our resources + community support, it'll keep getting better over time. https://ift.tt/Wd2UltZ June 10, 2026 at 09:39PM

Show HN: LocalCode – turn plain English into CLI commands with Apple's local AI https://ift.tt/5esybMi

Show HN: LocalCode – turn plain English into CLI commands with Apple's local AI https://ift.tt/YJzM96o June 10, 2026 at 02:34AM

Show HN: OpenYabby, voice-controlled multi-agent orchestrator for Claude Code https://ift.tt/xKOuhC9

Show HN: OpenYabby, voice-controlled multi-agent orchestrator for Claude Code https://ift.tt/oHZFjeJ June 10, 2026 at 01:38AM

Show HN: Transit-format (JSON/MessagePack) reader/writer in C https://ift.tt/fGB5ihJ

Show HN: Transit-format (JSON/MessagePack) reader/writer in C Transit.c is an addition to the set of libraries to support transit data interchange format written in C11. It supports full 0.8 specification of cognitect's transit-format: JSON, JSON-Verbose and MessagePack encodings, all ground and extension types, compression via keys caching, extensibility via custom tag handlers. https://ift.tt/etkdHVs June 8, 2026 at 03:05PM

Show HN: HTTP/3 and raw QUIC client/server APIs for Node.js https://ift.tt/ecnuEKb

Show HN: HTTP/3 and raw QUIC client/server APIs for Node.js I built this because I wanted to make outbound and accept inbound HTTP/3 and raw QUIC connections from ordinary Node.js code, without building Node from source or putting everything behind a reverse proxy. Repo: https://ift.tt/NXKcFUq npm: https://ift.tt/XnrOCqP It’s a native package around Rust/quiche. It supports both client and server APIs, I'm using it in a couple of projects: creating raw QUIC streams, datagrams, custom ALPN, session behavior, and HTTP/3 client work from Node. I've tried to be very safe in the native code, written in rust, with proofs around the parts I was most concerned about getting wrong. I have it hosting a couple of sites as HTTP3 endpoints and found it working well. https://ift.tt/NXKcFUq June 9, 2026 at 12:08AM

Show HN: Stop returning raw JSON from MCP servers, build rich inline UIs https://ift.tt/vH6b2Bj

Show HN: Stop returning raw JSON from MCP servers, build rich inline UIs https://ift.tt/mxs0wul June 9, 2026 at 12:07AM

Show HN: A Minecraft builder skill for coding agents https://ift.tt/R5DQ8I0

Show HN: A Minecraft builder skill for coding agents https://ift.tt/RaWLn4B June 8, 2026 at 08:21PM

Show HN: NoSuggest – Watch YouTube without the recommendation algorithm https://ift.tt/KkdOoMr

Show HN: NoSuggest – Watch YouTube without the recommendation algorithm NoSuggest is a quiet act of resistance against YouTube algorithms always trying to pull you into a loop of unlimited videos in turn into unlimited screen time. With unending side cards of videos, auto-play, what's next suggestions, YouTube shorts and notifications, users will be doom scrolling for many hours in a day. I faced the same problem. Acknowledging that, not all content in YouTube is bad. There are educational videos, genuine news contents without political bias which is very hard to find outside YouTube and many other good relaxing, entertainment stuff. NoSuggest lets you only follow the YouTube channels you like and removes all types of recommendation YouTube has. So you don't waste time on watching things which you never wanted to watch anyways. UI is very simple. You add your favourite channels in "Channels" tab and latest 5 videos per channel excluding shorts would appear in "Feed" tab. "Search" tab is to search for specific videos to watch and "Saved" tab is to bookmark any video you want to watch later. Intention of NoSuggest is to provide whatever is necessary to extract whats good from YouTube all inside NoSuggest and leave out bad parts. NoSuggest works in any devices. Install it as an app (PWA) in android and iPhone, or simply open in browser in laptops. No sign-in, no account creation or no card details. NoSuggest won't even ask your name. Total privacy for the users. Parents can add the channels and save some educational videos and lock it with the pin for kids mode. Kids won't be able access unwanted additive contents inside NoSuggest. Completely free, no string attached. Source available in Github through NoSuggest website. I would love genuine feedback. Thank you very much for your attention on this matter. https://ift.tt/DJYTmhR June 4, 2026 at 02:44AM

Show HN: An mkv player that uses WASM to render you videos https://ift.tt/pJjemUr

Show HN: An mkv player that uses WASM to render you videos hello HN i want to share this wasm experience i built for a universal mkv player on the web using wasm to ship a lean decoder only ffmpeg build, thus way codecs unsupported by the browser can be played I wonder if this holds any value to anyone anymore https://parallax.kinosoft.moe/ June 8, 2026 at 05:27AM

Show HN: I Derived a Pancake https://ift.tt/MNrBp83

Show HN: I Derived a Pancake After 25 years of making other people's pancake recipes - always yearning for more tang, more fluff, and more predictability - I decided to derive the pancake recipe from the chemistry. You mark checkboxes for what you have on hand (ricotta, sour cream, kefir, buttermilk, yogurt, cottage cheese, lemon, cream of tartar, etc.) and it computes the best recipe based on targets for acid, fat, salt, sugar, and CO2. My particular favorite are the yeast-raised lemon ricotta kefir pancakes - the best I've ever had. The math is done in a small pure-ESM library: ingredient composition to component masses and acid moles, a stoichiometry layer, and a bisection solver for the target deficits. I'm not a chemist, so if something is off, tell me and I will fix it! https://ift.tt/05n2zxX June 5, 2026 at 12:12PM

Show HN: Nightwatch, The open-source, read-only AI SRE https://ift.tt/84AakcH

Show HN: Nightwatch, The open-source, read-only AI SRE nightwatch is a local-first, read-only layer on top of your monitoring. it groups alert storm into incidents, flags noisy checks and has an agent that can investigate for you live systems. You can e.g. jump from the incident into the agent directly. the reason for this weekend project is that we had a kubernetes upgrade that went wrong, and at some point a rollback wasn't possible anymore, so it had to be fixed live during the night while several problems came together. We run a lot of different systems, on-prem and several Kubernetes clusters, and in a situation like that you spend most of the time just figuring out what is actually broken and where. So i thought that it would be pretty cool to have eyes in the dark in each system that can talk to your "brain". so the idea is to put a baby owl into each environment. Each owl runs where the systems live, keeps that environment's credentials local, and only dials outbound to a central brain, so there is no inbound hole into prod. It exposes a set of read-only skills, and the agent uses them to gather evidence and form a root-cause hypothesis, so the on-call engineer starts with a head start instead of from zero. read-only for now, i don't trust it near prod yet and honestly neither should you. llocal-first for easy self-hosting and to keep credentials on your side. the clustering and recommendations run fully offline with no llm at all. the agent needs a tool-calling llm, you can point it at a remote one, or self-host one (ollama etc.) if you want to stay fully offline. for non selfhosters: before every remote llm call, nightwatch strips real secrets (unrestorable) and swaps identifiers like ips, hostnames and paths for reversible placeholders, so the model only sees masked data while real values are restored only in the proposed commands and tool calls Would love if you try it in your Systems https://ift.tt/sM5IZ8X June 8, 2026 at 01:54AM

Show HN: Dap-mux – Connect your editor and REPL to the same debug session https://ift.tt/iw4onjx

Show HN: Dap-mux – Connect your editor and REPL to the same debug session I have been coding over four decades, in many languages, on many projects (including Firefox, Final Cut Pro, the Newton, and Fullwrite Professional if you can remember that far back; all these using my "dead-name"). I wrote something small and simple to scratch an itch. It's the UNIX philosophy: small "one-trick ponies", each *really* good at their one trick, then the user can hook them together to solve actual problems. I'm a CLI guy, and for almost everything, I already have this. But not for debugging. The itch I scratched was the connector that enables this philosophy for debugging. That thing is dap-mux. A DAP multiplexer turning a one-to-one protocol into a cooperating session of as many tools as you need to get it done! How it started: Helix and Python for me (and sometimes IPython), with the rest of my team using PyCharm (which I have long loved!). My team's problem is that they want the PyCharm debugger, and so must be satisfied with the JetBrains editor. *My* problem was I could use a full-blown debugger *or* I could have IPython *or* I could have Helix (or sometimes an unsatisfying combination of Helix and the debugger). That was my "itch". DAP (Debug Adapter Protocol) is the tantalizing answer, except it isn't. DAP is what editors (that don't want to write their own debuggers) are starting to adopt. The problem with DAP is it's one-to-one. One editor connects to one debugger. Done. Not a solution to my problem. And then suddenly, it *was* the solution. I realized that a DAP multiplexer would let you connect any DAP-aware editor to any debugger for any language, and simultaneously to a REPL, another session of your editor (or a different editor)! With the side benefit that now, like screen or tmux, since each process is its own thing: sessions are durable. Just restart whatever crashed and you're back where you were! There were hard parts: sequencing, late joiners, state management. Different end-points working on different actions in different sequences but with the same message ids. I solved these problems something like how NAT works. Instead of translating network addresses, though, I'm translating the sequence numbers of each client into something global and ordered, then correctly routing replies back to the end-point awaiting them, while mapping the sequence numbers for those replies back into the space of that end-point. Knowing the current state of the debugger, and replaying that as a message sequence to late joiners lets you start/connect the clients in any order. I chose Python: asyncio fits the I/O-router pattern perfectly, and it lets the IPython extension run in-process rather than over IPC. There are problems not yet solved: for instance, I think configuration in the clients and/or the startup sequence is too complicated. But it functions! I got what I wanted! The combination I use every day: Python + debugpy + Helix + IPython, all connected simultaneously. Step with `%n` or `%s`, evaluate expressions with `%eval`, watch Helix track the current line in real time. Rust with codelldb is the second confirmed combination — I debugged a Dijkstra implementation with Helix and a third-party DAP observer tool both connected to the same codelldb session. A community member, Sean Perry, has already built [dap-observer]( https://ift.tt/J94PEKy ), which renders the current frame's variables as a navigable terminal tree. *This* was my exact dream! Small, focused, connectable tools all playing together! There's so much left to try: other editors, other debug adapters, Windows, other languages. None of this has been touched yet. The most helpful thing now is people testing it with their own setup and reporting what they find. It's time to play! `uv tool install 'dap-mux[ipython]'` for Python + IPython. `uv tool install dap-mux` for headless use with any language and adapter. No need for any part of the Python ecosystem. https://ift.tt/y298GJA June 7, 2026 at 02:43AM

Show HN: Typedframes – Pandas/polars column name checking at lint time https://ift.tt/vEfYhgJ

Show HN: Typedframes – Pandas/polars column name checking at lint time https://ift.tt/kCsAiWf June 7, 2026 at 02:02AM

Show HN: Resonate – Low-latency, high-resolution spectral analysis https://ift.tt/fQDC9rE

Show HN: Resonate – Low-latency, high-resolution spectral analysis Last April I shared about my Resonate project here ( https://ift.tt/K5OdwQE ) A lot has happened since: the work I presented in much more detail at last June's International Computer Music Conference (ICMC) got best paper award. I also gave a talk at the Audio Developer Conference in Bristol last November, the video is on YouTube). This year's work, which I recently presented at this year's ICMC, starts with known techniques from the phase vocoder literature to build self-tuning filter banks that extract very efficiently the frequency components that are actually present in the input signal. Overview on the project website, more details in the papers, including applications to super-resolution spectrograms and re-synthesis experiments. As many people have pointed out, none of the techniques I have used are new (some of them even have different names across different fields), but I haven't seen them applied together in this way, and to me the results are incredibly satisfying and sometimes look magical. See for example this demo: https://youtu.be/LasdoIJJkw8 Of course the best way to experience in person is through the free demo app: https://ift.tt/fOUHniM Looking forward to feedback from the community! https://ift.tt/4vNn3mI June 6, 2026 at 11:39PM

Show HN: I nerfed our coding agents on purpose https://ift.tt/btRQN9j

Show HN: I nerfed our coding agents on purpose Tl;dr: I trained a classifier to route to the least expensive model and reasoning depth to complete the request. Coupling that with additional automated token efficiency techniques has yielded 3x usage for the same spend. For anyone interested in trying it themselves: https://nerfguard.com Various teammates and I switched over to Codex from Claude Code recently. We still bounce between the tools, but Codex’s speed and steerability coupled with performance gains were hard to ignore. One of the downsides was that the per token pricing kicked in way sooner. This is happening across the board, but we felt it in Codex more acutely. We’re a startup filled with people who work around the clock and are obsessed with building — naturally our daily bill alone was striking. Luckily we’re going after a big mission and speed matters significantly more than marginal token spend on the edges. Still, it got us thinking about how it was ludicrous that while our product has a side effect of decreasing token spend and speeding up agentic workflows by many orders of magnitude, we were using these top tier models for all types of internal coding tasks without any of those optimizations. The waste felt pretty ridiculous — the most glaring culprit was that we were seemingly using the max intelligence model on max reasoning for every task even when the task clearly didn’t require it. As a company who spends a lot of time on cached intelligence, it was also easy for us to see how there was plenty of other low hanging fruit as well. So, on a recent weekend, I quickly built a tool to optimize our usage. At its core is a very fast classifier that classifies your requests to the least intelligence required for the task and includes some nice token optimizations on top. The result is roughly the same quality for multiples lower token spend. But even more exciting for us, is that the properly bin packed intelligence and reasoning levels meant our speed also went up considerably. This wasn’t negligible. We’ve observed up to 3x savings and hours per day per person in saved time that we would have otherwise been waiting on tool turns and coding agent responses. For us, that means improved engineering velocity and significantly higher usage for the same spend. It also means more usage before getting throttled. As I told friends about this, they also wanted to start using it to maximize the usage they could get out of their coding agent plans. There are now engineers across many of the most cutting edge AI companies using this tool to optimize their token utilization in this way. Not just to save money, but to maximize output. Turns out that the best way to avoid getting nerfed by Claude is to intentionally nerf yourself selectively. We decided to release it for the rest of the builder community to use as well. You can now turn on Nerfguard for yourself and start getting more usage today. June 6, 2026 at 04:49AM

Show HN: I rebuilt a tiny old volleyball game I loved https://ift.tt/lZQObdh

Show HN: I rebuilt a tiny old volleyball game I loved https://volleyhop.com/ June 6, 2026 at 01:42AM

Show HN: Bash Runtime for AWS Lambda https://ift.tt/je8JKH7

Show HN: Bash Runtime for AWS Lambda Hi HN, I built a Bash runtime for AWS Lambda to make writing glue code simpler and faster. Sometimes, all you need is a bit of `sed`, `awk`, maybe a loop and a few HTTP API calls, and this runtime gives you all the tools to do that. It comes bundled with `jq` and `curl` so you can handle JSON payloads and string together HTTP API calls right out of the box, including calling AWS services with `curl --aws-sigv4`. In keeping with the theme, the Lambda handler contract is also made as simple as practical: read from stdin, write to stdout, return 0 for success and non-0 for error. You can run shell scripts, call binaries (either what's available in `al2023.provided` or you can package your own static binaries with your handler), or a combination of both. If you remember nodding along to Adam Drake's post about how bash and coreutils can be faster than a Hadoop cluster, I hope you give this a whirl and find it useful. The runtime is packaged as a Lambda layer, so it should drop right into your normal AWS infrastructure. https://ift.tt/PwmT07U June 6, 2026 at 12:42AM

Show HN: Bot or Not – Spot AI-generated randomness https://ift.tt/fnPoJVI

Show HN: Bot or Not – Spot AI-generated randomness https://play-bot-or-not.vercel.app/ June 5, 2026 at 01:26AM

Show HN: Using Haskell to play music on 3D printer motors (2020) https://ift.tt/UJX25Gb

Show HN: Using Haskell to play music on 3D printer motors (2020) https://lucasoshiro.github.io/software-en/2020-07-31-music_gcode/ June 5, 2026 at 01:37AM

Show HN: Cost.dev (YC W21) – making agents cost-aware and cheaper to call https://ift.tt/2zao37s

Show HN: Cost.dev (YC W21) – making agents cost-aware and cheaper to call We launched Infracost on HN five years ago ( https://ift.tt/cuE04hU ) where our CLI generated cost estimates for infra-as-code, e.g. "this Terraform PR adds $400/mo". The idea was to shift cloud costs (FinOps) left, so engineers get visibility of costs before deployment and make better decisions. Earlier this year we started seeing agent traffic in our logs and it looked like coding agents were calling our CLI. But that CLI wasn't designed with coding agents in mind. We went down a philosophical rabbit hole to see if a CLI is even needed anymore given that Claude, Copilot et al. already follow best practices. Ultimately we decided to create a new CLI from the ground up with coding agents in mind for two reasons: 1. We optimized the CLI for agent callers and cut Claude's output token usage by up to 79% and API cost by up to 67% versus a bare-Claude baseline. We wrote a blog documenting our lessons on optimizing user token usage when designing a CLI, e.g. using predicate flags so the agent doesn't compose jq | python | wc pipelines, output format that strips JSON's redundant field names. The blog is here: https://ift.tt/BJ5v8oy... 2. With cloud costs, precision matters. Telling a coding agent "make this Terraform cost-optimized" can be expensive and lossy. You burn tokens loading code and policy context into every conversation. Your agent could make up a price and you wouldn't know because it's difficult to verify that across the ~10M price points that AWS, Azure and Google have. The CLI runs static analysis on the code, uses the latest prices from cloud vendors, and passes that context to the coding agent. So that's what we're launching today - Cost.dev: https://cost.dev/ . - It runs locally. Your code never leaves your machine, you get a fast feedback loop, and you're not burning API calls per character when you want to fetch prices. - The CLI does the deterministic work. Fetching price points, scanning the code, validating fixes. The coding agent does the natural-language part. You don't have to trust the LLM to remember the rules, and can verify it called the right CLI command. - It provides a consistent rule layer across every tool you use. Get cost estimates in your IDE and your coding agent with a single install. We support Claude Code, GitHub Copilot, Cursor, Windsurf, OpenAI Codex, Gemini CLI, as well as IDEs like VS Code and JetBrains Before we keep building more in that direction, I want to sanity-check with HN: is "agents writing IaC in prod" actually a thing yet, or am I betting on a future that's still a year out? I know software developers are using coding agents heavily, but are platform/infra folks doing that for prod too? Also, if you have any feedback on Cost.dev, I'd love to hear it! https://cost.dev/ June 4, 2026 at 05:00PM

Show HN: Fork of Rsync https://ift.tt/wdAXWp3

Show HN: Fork of Rsync Hello. After hearing of the problematic LLM commits in rsync, I made a fork of rsync. I decided to fork it off release 3.4.1, since I heard that's the last release without the LLM code. https://ift.tt/z3wt1HF June 4, 2026 at 03:50AM

Show HN: Lint Your Markdown with ESLint https://ift.tt/FWBysn8

Show HN: Lint Your Markdown with ESLint https://ift.tt/6RYJpEj June 3, 2026 at 07:17PM

Show HN: I created a React alternative using web componnents https://ift.tt/OEFeqBC

Show HN: I created a React alternative using web componnents https://ift.tt/pDOQrvE June 4, 2026 at 01:30AM

Show HN: 100cc - Roll your own Claude in 100 lines https://ift.tt/1pUvIid

Show HN: 100cc - Roll your own Claude in 100 lines https://ift.tt/ZxTPAUn June 3, 2026 at 12:05AM

Show HN: RePlaya – self-hosted browser session replay with live tailing https://ift.tt/SlPWbYB

Show HN: RePlaya – self-hosted browser session replay with live tailing Hi HN, I'm one of the founders of s2.dev. RePlaya ( https://ift.tt/rFoZEvL ) is a self-hosted browser session replay tool using rrweb ( https://ift.tt/8GK1tlS ). It occurred to me that a durable stream per session would be a much neater architectural foundation for much of what you'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. The alternative architecture is likely an ingest firehose which is then indexed, with associated complexity and latency. You'd have to string together multiple data systems like a message queue, a metadata database, and blob storage and/or an OLAP database. Here the only dependency is S2, which has an open source version you can self-host called s2-lite ( https://ift.tt/x7XRdC9 ). How it works: - one S2 stream per browser session - large rrweb events (like a full snapshot) get framed across multiple binary S2 records and reassembled on read - active sessions are tailed with an S2 read session, and bridged to the browser over SSE - session listing relies on stream names encoding reverse timestamps, as S2 returns a lexicographic order listing - relying on fencing tokens so a stopped session can't be written to again by a late recorder - retention and GC are handled via S2 stream config, so no background job needed Curious to hear from folks on the tool or the stream-per-session model! https://ift.tt/rFoZEvL June 2, 2026 at 11:10PM

Show HN: A free Linux adaptation of NETworkManager by BornToBeRoot https://ift.tt/wsKYJnz

Show HN: A free Linux adaptation of NETworkManager by BornToBeRoot https://ift.tt/ahr7bKS May 30, 2026 at 10:10PM

Show HN: Dataroom – a Pi and self-hosted research harness on low-budget GPU https://ift.tt/Dnlj7hd

Show HN: Dataroom – a Pi and self-hosted research harness on low-budget GPU https://ift.tt/XcY6awg June 2, 2026 at 03:06AM

Show HN: Trumpstonks – every company Trump's named, backtested vs. the S&P https://ift.tt/xV19vZk

Show HN: Trumpstonks – every company Trump's named, backtested vs. the S&P https://ift.tt/eZLqYHN June 1, 2026 at 11:00PM

Show HN: Textile – A desktop app for weaving together bits of text https://ift.tt/EToKwFB

Show HN: Textile – A desktop app for weaving together bits of text Hi all, I'm excited to show off Textile, a desktop app I recently built. Textile can combine bits of text using various inputs, such as commands on your computer, the contents of your clipboard, and hard-coded strings that you provide. It lets you carefully build up and modify a dynamic string, step by step, until it's exactly how you need it. The saved steps can then be executed on demand, with the click of a button or using a keyboard shortcut. I built Textile because I was often constructing complicated, dynamic URLs from various sources that all existed on my computer. I got tired of manually switching between different apps, copying and pasting various chunks of text, and assembling them all together somewhere. I've also found Textile to be quite useful as a kind of repository for obscure bits of static text, such as ½ and other fraction characters, when I can't be bothered to remember their built-in keyboard combinations. I also built Textile because I wanted to learn Electron, although I expect there will be some gnashing of teeth about this here. :) I think desktop development is quite interesting, in part because it doesn't require me, the developer, to pay for an API server and database in the cloud. The app itself is both the UI and the "server," and the local drive is effectively the "database." I knows this trades away syncing with the cloud but, on the other hand, there's something nice about knowing that your files are on your drive and not on somebody else's server. I realize that something like Textile may already exist, and may have much more functionality but, again, I wanted to learn. I must say that multi-sequence keyboard shortcuts are hard, and there are cases that don't work right in Textile. I feel vulnerable admitting that my approach has much room for improvement! For what it's worth, I did not use an LLM to write any code for Textile (although I did ask many questions of an LLM, as an alternative to Googling). Textile is open source, free to use, and does not require sign up, email, phone, or other such barriers. Try it and let me know what you think! (Note: I don't have access to hardware running Windows or Linux, so Textile is only available for macOS at the moment.) https://ift.tt/98P4fDz June 2, 2026 at 12:24AM