Show HN: Logcat.ai:AI-powered observability for Operating Systems(Android+Linux) https://ift.tt/b6IV74D

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

Pride Month Staff Spotlight: Driven to Create Inclusive Communications

Pride Month Staff Spotlight: Driven to Create Inclusive Communications
By Glennis Markison

Nehama Rogozen has created inclusive outreach campaigns for several SFMTA projects. All year long, LGBTQ+ staff members across our agency help keep our transit system running and our streets safe. This Pride Month, we want to recognize their impact. Today, we feature Nehama Rogozen, a public relations officer at the SFMTA. Learn why she's so driven to meet our high standard of inclusive outreach – and how it benefits both the public and our staff. Making space for every voice Rogozen has worked at the SFMTA for six and a half years. She started on our Customer Service team and learned a lot...

Published June 24, 2025 at 05:30AM
https://ift.tt/kPQrdoz

Show HN: I built a tool to create App Screenshots https://ift.tt/fW7uZed

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/7yz2VNM June 25, 2025 at 01:07AM

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

Show HN: Comparator - I built a free, open-source app to compare job offers https://ift.tt/e2C5PKW 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/tXjQE2g

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

Show HN: TNX API – Natural Language Interactions with Your Database https://ift.tt/0dMa7SX

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/uMcSOWt 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/uMcSOWt (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/uMcSOWt June 24, 2025 at 12:48AM

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

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/qbRWFS3... 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/LXYQ4OT We'd greatly appreciate any feedback you have and hope you get the chance to try out Pickaxe. https://ift.tt/7DmxZ94 June 20, 2025 at 09:37PM