Show HN: Logcat.ai:AI-powered observability for Operating Systems(Android+Linux) https://ift.tt/W8b60Oz

Show HN: Logcat.ai:AI-powered observability for Operating Systems(Android+Linux) Hello HN! I'm an Android OS engineer. I've worked with AOSP and Linux kernels all my career and always wondered about lack of sophisticated tools to debug and analyze system-level logs. Always had to resort to manually skimming through large log files to find something I needed to. With the rise of LLMs and the AI-age, I felt it was a great opportunity to build something for OS engineers, which is what led to logcat.ai! We are building the industry-first observability platform for system level intelligence. Think "Datadog for operating systems" instead of applications. Currently, we support Android and Linux - more platforms on the way. With Android we offer: 1. logcat analysis: Ability to analyze logcat logs for root cause analysis of system issues with natural language search. Unlike, Firebase which is an app-level observability, logcat.ai provides intelligence at OS level spanning bootloader, kernel and framework layer. 2. bugreport analysis: As you know a bugreport is a super-verbose snapshot of an Android OS collected at a point of time. Analyzing these logs takes hours and sometimes even days. We are working to bring this down to minutes! Analysis of memory, cpu, process stats to infer memory pressure levels, system stress, and nail down the processes responsible for it, identify performance bottlenecks and memory leaks across the system. For Linux we offer: dmesg (kernel log) analysis to help identify issues at Linux kernel level. We plan to add support for different Linux distros with their own logging pretty soon. Our goal is to build a single-pane-of-glass observability experience for operating systems worldwide, something that's never been done before. Our website may not reflect all the features a.t.m but we have a lot of things cooking! Ask us anything. We are providing free beta access for a period of time. We'd love your feedback and comments on what you think about logcat.ai! https://logcat.ai June 24, 2025 at 10:53PM

Show HN: I built a tool to create App Screenshots https://ift.tt/YRBh2O3

Show HN: I built a tool to create App Screenshots I built a tool to create stunning App Store & Google Play Screenshots. https://ift.tt/pqAPHJo June 25, 2025 at 01:07AM

Show HN: Comparator - I built a free, open-source app to compare job offers https://ift.tt/4WPqNx6

Show HN: Comparator - I built a free, open-source app to compare job offers https://ift.tt/lzWGYP4 June 24, 2025 at 05:30AM

Show HN: I made a fun quiz that reviews last week's top posts on r/programming https://ift.tt/B9LGim7

Show HN: I made a fun quiz that reviews last week's top posts on r/programming https://ift.tt/ksPxrYC June 24, 2025 at 02:18AM

Show HN: TNX API – Natural Language Interactions with Your Database https://ift.tt/CODRGBt

Show HN: TNX API – Natural Language Interactions with Your Database Hey HN! I built TNX API to make working with databases as simple as asking a question in plain English. What it does: - You write a natural language prompt (e.g., "List products with price > 20 USD") - Our system turns it into SQL and runs it - You get actual results, optionally visualized - Your data stays private – nothing is stored, the AI doesn‘t see it, and the API forgets immediately after replying Why I made this: Writing SQL for routine questions is https://ift.tt/Pxs9wDm still a blocker for many teams. I wanted a privacy-first, plug-and-play API that just works with natural language. TNX doesn’t just translate — it executes the queries and returns actual answers (not just SQL). Examples: - You ask: “Total sales by product category this year?” → TNX replies: [furniture: $43,000, electronics: $12,000] + “Want a chart for this?” - You ask: “Which customers didn’t order in the last 90 days?” → TNX replies with names or IDs and offers follow-up actions Notes: - Built on modern AI models (small + fast) - No need to send full database dumps – just metadata/config + real-time access - Easy API integration - (Bonus: If you should be interested, I‘d handle setup + customization for you) Try it out: https://ift.tt/Pxs9wDm (user name: „hi@tnxapi.com“, password „1“ (so it's harder to forget)) (example promts: - „Please give me the name, ShortDescription and price of product with idpk = 20.“ or - „Please list me all product prices from idpk 10 to 20.“ and then - „Please list me all product prices from idpk 10 to 20.“ (I copied some of my databases for this test, I am sorry for the data being in German xd)) Cheers, Lasse Tramann (Feel free to reach out to hi@tnxapi.com : ) ) https://ift.tt/Pxs9wDm June 24, 2025 at 12:48AM

Show HN: Pickaxe – a TypeScript library for building AI agents https://ift.tt/xwy4g1K

Show HN: Pickaxe – a TypeScript library for building AI agents Hey HN, Gabe and Alexander here from Hatchet. Today we're releasing Pickaxe, a Typescript library to build AI agents which are scalable and fault-tolerant. Here's a demo: https://ift.tt/x1tAp7q... Pickaxe provides a simple set of primitives for building agents which can automatically checkpoint their state and suspend or resume processing (also known as durable execution) while waiting for external events (like a human in the loop). The library is based on common patterns we've seen when helping Hatchet users run millions of agent executions per day. Unlike other tools, Pickaxe is not a framework. It does not have any opinions or abstractions for implementing agent memory, prompting, context, or calling LLMs directly. Its only focus is making AI agents more observable and reliable. As agents start to scale, there are generally three big problems that emerge: 1. Agents are long-running compared to other parts of your application. Extremely long-running processes are tricky because deploying new infra or hitting request timeouts on serverless runtimes will interrupt their execution. 2. They are stateful: they generally store internal state which governs the next step in the execution path 3. They require access to lots of fresh data, which can either be queried during agent execution or needs to be continuously refreshed from a data source. (These problems are more specific to agents which execute remotely -- locally running agents generally don't have these problems) Pickaxe is designed to solve these issues by providing a simple API which wraps durable execution infrastructure for agents. Durable execution is a way of automatically checkpointing the state of a process, so that if the process fails, it can automatically be replayed from the checkpoint, rather than starting over from the beginning. This model is also particularly useful when your agent needs to wait for an external event or human review in order to continue execution. To support this pattern, Pickaxe uses a Hatchet feature called `waitFor` which durably registers a listener for an event, which means that even if the agent isn't actively listening for the event, it is guaranteed to be processed by Hatchet and stored in the execution history and resume processing. This infrastructure is powered by what is essentially a linear event log, which stores the entire execution history of an agent in a Postgres database managed by Hatchet. Full docs are here: https://ift.tt/Nxr2qwe We'd greatly appreciate any feedback you have and hope you get the chance to try out Pickaxe. https://ift.tt/JqFZiPp June 20, 2025 at 09:37PM

Show HN: Lazycontainer: A Terminal UI for Apple Containers https://ift.tt/PV92Zpt

Show HN: Lazycontainer: A Terminal UI for Apple Containers Apple finally released native support for Containers, but it's missing a terminal UI. I'm building this TUI to make managing Apple containers easy, just like lazydocker made it easy to manage all things Docker. Existing Docker compatible TUIs do not support Apple containers. The current version has support for managing containers and images. Feedback, issue reports, and PRs are appreciated :) https://ift.tt/odFAbuL June 23, 2025 at 12:14AM

Show HN: Stacklane – GitHub App for Stacked PR Clarity https://ift.tt/KHACtgr

Show HN: Stacklane – GitHub App for Stacked PR Clarity https://stacklane.dev June 23, 2025 at 12:25AM

Show HN: Turn a paper's DOI into its full reference list (BibTeX/RIS, etc.) https://ift.tt/JHyYEzi

Show HN: Turn a paper's DOI into its full reference list (BibTeX/RIS, etc.) https://ift.tt/uW6yqlX June 22, 2025 at 11:55PM

Show HN: Good old emails and LLMs for automating job tracking https://ift.tt/sfXKBay

Show HN: Good old emails and LLMs for automating job tracking So I spent the last few days building Jobstack. The logic is quite simple. You apply to jobs and you get emails, you trade emails back and forth from interviews, questions and others until the role is either accepted or you are rejected. Also easy to apply to hundreds of roles and not being to know where you stand easily. With Josbtack, you sign up, get a unique email and forward emails to the url. And it uses LLMs to extract company details , tries to find information online about them and presents that to you. Every email you forward becomes part of your timeline with the company. It also tracks rejection, offers from the emails too and gives you a nice stats dashboard amongst others. Using Gemini 2.5 pro right now. No data stored not in any way. After extraction, it’s discarded. Even “AI chats with the company” aren’t stored https://jobstack.me June 22, 2025 at 03:07AM

Show HN: To-Userscript: Chrome Extension to Userscript Converter https://ift.tt/QC6evkV

Show HN: To-Userscript: Chrome Extension to Userscript Converter https://ift.tt/yumrP79 June 22, 2025 at 12:55AM

Show HN: Swift UI app for extracting beer information by just taking photos https://ift.tt/154chTk

Show HN: Swift UI app for extracting beer information by just taking photos I would like to share Swift UI app for extracting beer information by just taking photos. It is based on Gemini API and you can easily use this as reference to create an AI supported iOS app. https://ift.tt/1j6Mniw June 21, 2025 at 03:49PM

Show HN: Inspect and extract files from MSI installers directly in your browser https://ift.tt/qrcbR81

Show HN: Inspect and extract files from MSI installers directly in your browser Hey everyone! I'm excited to share a small web app I built that allows you to view and extract the contents of Windows MSI installers directly in your browser. It's essentially a web-based "lessmsi" powered by Pyodide. You can try it out at: https://ift.tt/yxJG1fE My motivation for building this was from part of my day job -- I often get Windows MSI installers and need to extract files while preserving the relative directory structure and filenames, as they would appear after a full installation. The existing tools I found were good but limited in which platforms they support: lessmsi works great on Windows, while msitools works for Linux/macOS. Neither is a truly cross-platform solution that works on any major OS. So we developed pymsi (a pure Python library, available on GitHub at https://ift.tt/t1ElQix ) to handle reading and extracting MSI files from Python. Then I realized that since pymsi has no native dependencies, it could potentially run in a web browser using Pyodide. After a bit of "vibe coding" and fixing some "hallucinated" functions/classes that don't exist in pymsi, the result was this client-side web app. If you need an MSI file to experiment with, older versions of PowerToys included the installer in .msi form, such as this one: https://ift.tt/2xUVukg.... Note that the underlying pymsi library hasn't been extensively tested against a bunch of MSI installers yet, so there might still be lingering bugs. If you come across any issues, please don't hesitate to report them in on the GitHub repository ( https://ift.tt/aFuhP0x ). I'd love to hear your feedback and answer any questions! https://ift.tt/yxJG1fE June 21, 2025 at 01:34AM

Show HN: Vpuna AI Search – A semantic search platform https://ift.tt/Mftw5r6

Show HN: Vpuna AI Search – A semantic search platform Dear HN Community, I am a long time fan and first-time contributor. I just launched a developer focused semantic search platform and wanted to share it with the community. The idea is simple: upload structured or unstructured documents, select the fields you want to index and tag as metadata, and instantly get a clean search API you can use in your own app. Here is what it currently supports: - Manage your own tenants and projects - Upload .json and .txt files (support for .pdf, .docx, .xlsx, .yml, etc. coming soon) - Expose 3 APIs: search, upload document (embeddings), and delete document - Manage your own API keys - Uses CPU based sentence-transformers/all-MiniLM-L6-v2 for embeddings ( support for other local and online models are coming soon) LLM summarization and Model Context Protocol (MCP) support are on the roadmap Why I built it: In my consulting work, I kept seeing client wanting to move beyond basic keyword search and integrate semantic search with optional summarization. Most existing tools are either too expensive, too restrictive, or require custom layers (like custom Python servers for pre processing queries and embeddings). I wanted something API first, developer friendly, and easy to self host or use out of the box. This is the first release, and I would love your feedback. Would you use this? What is missing for your use case? Here is the README with all the links https://ift.tt/FgWhS1O Thank you for your time. https://ift.tt/OLc8kq9 June 20, 2025 at 11:24PM

Show HN: RM2000 Tape Recorder, an audio sampler for macOS https://ift.tt/X2oNpmG

Show HN: RM2000 Tape Recorder, an audio sampler for macOS RM2000 Tape Recorder makes it stupid simple to grab audio samples and organize them: just record the sample, give it a title (and maybe some tags), and it is saved neatly into a directory of your choosing. I'm a huge datahoarder and have always appreciated tools / services like PureRef and Are.na which help me make sense of everything I collect. Those services concern themselves with images and video - I wondered, why can't the same be done with music and audiofiles? I actually got the inspiration for the filenaming scheme from the Emacs Denote package - every sample is saved in the format of title--tag1--tag2.mp3. Emacs Denote does something similar, for example an identifier--title--keywords.org . I chose this method as any file browser with fuzzy search can search through samples, i.e. - the Ableton file browser. Just search up some of the tags, and a title, and you'll be able to find your sample. I wanted this app to look good, as well (and is why I spent so much time making it!) The app is made with a mix of SwiftUI and AppKit, while the assets were rendered in Sketch I appreciate your time and I'd love to hear your thoughts on it. If you do download it, and find suggestions / bugs, please let me know! Cheers https://rm2000.app June 17, 2025 at 09:50PM

Show HN: Relix: A Unix-like OS based on MIT's xv6 https://ift.tt/pRtFIyw

Show HN: Relix: A Unix-like OS based on MIT's xv6 Hello everyone, this is my first post as someone encouraged me to post this here. I have been working on Relix for over a year and am willing to answer any questions you may have! https://ift.tt/aql9pUR June 20, 2025 at 12:53AM

Show HN: AI Debate Arena – See Which LLM Argues Best https://ift.tt/94OmjDu

Show HN: AI Debate Arena – See Which LLM Argues Best Ever wish you could get the best arguments for both sides of a debate? I built an AI-powered debate platform that pits language models against each other on controversial topics. Each AI is randomly assigned a side (pro/con). You vote before and after to see if you were persuaded. Most content today presents lopsided arguments. They provide strong points for one side, weak ones for the other. This project aims to surface the strongest arguments from both sides, using LLMs to simulate a fair debate. With enough usage, I want to use it to benchmark LLMs. My hypothesis is that randomly assigning sides of the debate, models with built-in biases will score worse. It’s currently using GPT 4o, Grok 3, and Gemini 2.5 Flash. It’s early, still rough around the edges, and I’d love feedback on the concept and direction. Curious how the HN crowd thinks this could evolve. It’s built for the intellectually curious that are open minded about changing their positions. Some next steps I’m considering: - Tuning the length and structure of arguments - Prompting improvements to reduce rhetorical fluff - Optional audio output of debates Try it out and let me know what you think! https://ift.tt/wU6QRA2 June 19, 2025 at 01:56AM

Show HN: Turn long form videos into short form clips https://ift.tt/PyKjgk8

Show HN: Turn long form videos into short form clips https://ift.tt/iczmNZt June 18, 2025 at 11:22PM

Show HN: I couldn't poop, so I built an app to track digestion in real-time https://ift.tt/bgUfWBq

Show HN: I couldn't poop, so I built an app to track digestion in real-time https://ift.tt/ZNs2qSM June 19, 2025 at 12:02AM

Show HN: Superscan – Visualize filetree for filesystem, gdrive, S3 buckets etc. https://ift.tt/vKgmadI

Show HN: Superscan – Visualize filetree for filesystem, gdrive, S3 buckets etc. https://ift.tt/U9H8IQt June 18, 2025 at 02:52AM