Posts

Show HN: Radix – Visual UI for agentic programming https://ift.tt/otPUjxZ

Show HN: Radix – Visual UI for agentic programming Hey HN, I'm Jordan from Radix. Radix is a UI tool for programming agents. You prompt your agent to generate a workspace for a task you're working on and get an interactive widget that persists locally on disk. I built Radix because I always needed tools while I was writing code: tools to test little experiments, to play around with UI, to visualise results etc. Sometimes these would end up as python tools that read and plotted data, or separate React apps spun up just to test a single feature. Lately obviously I've been using Claude artifacts but these are quite limited. I wanted a system where it was easy to leave comments or adapt an artifact without having to give vague descriptions back to the agent, and where ideally I could actually shift away from a chat window as the main interface. I've got a pro version of Radix which I will launch soon. This current version is entirely free and is definitely a beta -- there w...

Show HN: Treepeat – Code similarity detection using Tree-sitter https://ift.tt/rQtmK1D

Show HN: Treepeat – Code similarity detection using Tree-sitter treepeat is a tool that finds similarities in your codebase. Find duplicate code blocks meaningful to the language (classes/functions), not just lines. Find near-duplicates: ignore whitespace, strings, high level AST nodes such as function and names. Find structurally similar code: anonymize identifiers, constants, etc. Pull requests welcome: This is very much an proof of concept - I'm happy with it, but I haven't supported very many languages at present. Languages supported: astro, bash, css, go, html, javascript, lua, markdown (plus codeblocks), python, sql, typescript, java, kotlin, rust, yaml https://ift.tt/tRNUga4 September 22, 2026 at 10:23PM

Show HN: Conway's Game of Life in boot sector https://ift.tt/MmhLiCW

Show HN: Conway's Game of Life in boot sector Hello HN! On these weekends, I was sitting and thinking about where our industry is going, and how fun it was earlier, when we wrote more code than chat messages. The thoughts quickly turned into a wish to build something like we did earlier. In my case, it ended up as something much "earlier" than I had in mind initially... So, Conway's Game of Life running from a 512-byte x86 boot sector. Maybe you will find it interesting. I tried to comment the code as much as possible, which might be especially useful if you are learning assembly. Have fun! https://ift.tt/QSstVEZ September 21, 2026 at 11:58PM

Show HN: I built a post-mortem debugger for native Windows x64/x86 crashes https://ift.tt/8p6o09U

Show HN: I built a post-mortem debugger for native Windows x64/x86 crashes Hello HN! I've spent years debugging Windows crashes with tools that were either friendly but limited (e.g. Visual Studio) or powerful but archaic (e.g. WinDbg). I developed patterns and methods for understanding what was going on, and decided to build it into a much more effective debugging tool called ForensicDbg. I built a modern interface to minimize the friction when debugging. All of the data shown to you is analyzed, interpreted, and presented to you clearly, so you can focus on what matters. Everything is interlinked so you can quickly and intuitivly navigate through the process space. ForensicDbg comes with an MCP server which allows for agenic debugging. The work done to interpret and interlink your data also benefits AI tools. It removes the risk of hallucinations while building a stable foundation for them to work from without spending tokens. If you want to try it out you can sign up and get a f...

Show HN: Crest – Answer Claude Code approvals from your MacBook's notch https://ift.tt/1NLMVxD

Show HN: Crest – Answer Claude Code approvals from your MacBook's notch https://ift.tt/P7SCvLk September 23, 2026 at 11:18PM

Show HN: JevBench, a reproducible benchmark for typed decision models https://ift.tt/aJrpRiv

Show HN: JevBench, a reproducible benchmark for typed decision models Hi HN! I built JevBench because Jev kicks ass, and the world deserves to know how the serious open source and fake lookalike projects really perform in comparison. Jev-class models return bounded choices and probabilities instead of text, and are disruptively faster and cheaper than LLMs, while being similarly intelligent on the text input they operate on. JevBench allows looking at accuracy, latency and price all at once, in a weighted way - you can even configure the weighting. A full run asks 534 English decisions. The v1.3 score combines chance-corrected Intelligence, Calibration, Speed and Cost. Leaderboard right now: #1 - Jev 74.4 #2 - SemIf 73.1 #3 - djev 73.0 #4 - Winnow-12B Q8 71.2 #5 reflex 4B 70.3. MIT harness, public items, frozen artifacts, scoring code and public per-task outcomes: https://ift.tt/UrTtuA0 Two no-signup demos: https://ift.tt/GuSOEt...

Show HN: Training a model to identify AI web content from structure alone https://ift.tt/6NCSTHX

Show HN: Training a model to identify AI web content from structure alone Hey HN! We’re Vincent and Jochen from Sitefire ( https://sitefire.ai ). We have been working together for years, with backgrounds in RL/optimization at Stanford and software engineering from Technical University Munich (TUM). With Sitefire (YC W26), we help marketing teams get recommended by AI Search (ChatGPT, Google AI Overviews, AI Mode, Claude, etc.). Our software monitors prompts, sees which web pages get cited, and uses these insights to help marketing teams take action, e.g. create YouTube videos or write the right blog posts. This means we have a commercial stake in AI-generated web content. And for now, high-information, AI-generated content works great to get cited and recommended in AI Search. But after talking to hundreds of marketing teams, it became clear that everyone despises AI-generated content (“AI slop”). And yet, everyone still wants to leverage AI to create content. So we asked ourselves: wh...