Show HN: Spotilyrics – See synchronized Spotify lyrics inside VS Code https://ift.tt/gIfjXZA

Show HN: Spotilyrics – See synchronized Spotify lyrics inside VS Code https://ift.tt/KMOjwYX September 1, 2025 at 04:39AM

Show HN: Pol/ite – /pol/ but posts are all polite https://ift.tt/qKYghr7

Show HN: Pol/ite – /pol/ but posts are all polite What woud it be like to read fringe political views forcibly made polite by way of LLM? System prompt (gemini-2.5-flash-lite): "You are rewriting 4chan posts to be more polite while preserving their original meaning and tone. Don't add unnecessary verbosity; keep it concise. Make sure to preserve formatting including markdown, links and greentext." https://pol-ite.web.app August 31, 2025 at 09:52PM

Show HN: Oaki–job finder and resume maker https://ift.tt/chCel9U

Show HN: Oaki–job finder and resume maker Hi! I built Oaki about a year ago as a side project to solve my own frustration with job applications, and it’s now helping thousands of users with their job hunt. I had quit my previous (consulting) company when I decided to step back into the job market, and I HATED applying to jobs with a passion. Finding good jobs, sifting through all the crap, etc.etc. So I built a rough MVP and posted it on Reddit and got more paid users than I ever had with any other company/startup I was in. To top that off, I found a really awesome job (and landed many more interviews) with it, so I know from first-hand experience that it works! Oaki’s 3-step flow: 1. Import or build a modern, eye-catching resume in under 2 minutes with Oaki 2. Set preferences (role, location, salary, and more) 3. Oaki finds best-fit jobs daily, generates a slightly tailored resume for each, designed to amplify each users' uniqueness On that last point, we're really big on safe AI use; that means we never use it for spam or 'spray and pray' applications. On the surface it looks pretty simple, but Oaki is powered by some really cool tech, blending ML with LLMs, orchestration, hybrid search, and much much more from finding jobs to printing high quality dynamic resumes, and even helping you apply to jobs. While the job finder itself is free (and all accounts get a free no-credit card trial), I do have to charge people for the AI-generated resumes/applications part. For anyone who needs it or knows someone, I hope it can help with the job search; it's reeeally bad right now. You can also use code `ICAMEFROMHN20` to get 20% off, or DM/email me at nour@oaki.io (I read everything). Cheers! Nour https://www.oaki.io/ September 1, 2025 at 12:37AM

Show HN: Sometimes GitHub is boring, so I made a CLI tool to fix it https://ift.tt/oOyVxdF

Show HN: Sometimes GitHub is boring, so I made a CLI tool to fix it Just wanted to clone a repo from my gh account and visualize it. Pretty easy with gitact. You can check any gh account. It’s called { gitact } quickly navigate through a user’s repos instantly grab the right git clone URL Feedback, stars and PRs are welcome https://ift.tt/W5c2X6u August 31, 2025 at 02:26AM

Show HN: An AI coding tool for unserious projects https://ift.tt/uSgXVtq

Show HN: An AI coding tool for unserious projects Crazy Context is a playful no-code tool to generate project prompts, then turn them into Javascript-based applications in one shot. It has robust version control and a unique approach while super easy to use, cheap and fast. It's perfect for any trial and error type approach. https://ift.tt/JuvTZ5r August 31, 2025 at 02:35AM

Show HN: Give Claude Code control of your browser (open-source) https://ift.tt/gqHIAp9

Show HN: Give Claude Code control of your browser (open-source) As I started to use Claude Code to do more random tasks I realized I could basically build any CLI tool and it would use it. So I built one that controls the browser and open-sourced it. It should work with Codex or any other CLI-based agent! I have a long term idea where the models are all local and then the tool is privacy preserving because it's easy to remove PII from text, but I'd definitely not recommend using this for anything important just yet. You'll need a Gemini key until I (or someone else) figure out how to distill a local version out of that part of the pipeline. Github link: https://ift.tt/DESQj6r https://www.cli-agents.click/ August 30, 2025 at 11:37PM

Show HN: Readn – Feed reader with Hacker News support https://ift.tt/sbWjGkC

Show HN: Readn – Feed reader with Hacker News support This feed reader can fetch and display discussion threads from Hacker News and Lobste.rs, making it convenient to follow both articles and the conversations around them. It’s a fork of the original Yarr project, whose author considers it feature-complete and is no longer accepting feature requests. https://ift.tt/7bv16jl August 30, 2025 at 12:01AM

Show HN: An open source implementation of OpenStreetMap in Electron https://ift.tt/mMcb5I0

Show HN: An open source implementation of OpenStreetMap in Electron https://ift.tt/ZhHvrs5 August 30, 2025 at 02:14AM

Show HN: Magic links – Get video and dev logs without installing anything https://ift.tt/y1eFPxo

Show HN: Magic links – Get video and dev logs without installing anything Hey HN, For a while now, our team has been trying to solve a common problem: getting all the context needed to debug a bug report without the endless back-and-forth. It’s hard to fix what you can't see, and console logs, network requests, and other dev data are usually missing from bug reports. We’ve been working on a new tool called Recording Links. The idea is simple: you send a link to a user or teammate, and when they record their screen to show an issue, the link automatically captures a video of the problem along with all the dev context, like console logs and network requests. Our goal is to make it so you can get a complete, debuggable bug report in one go. We think this can save a ton of time that's normally spent on follow-up calls and emails. We’re a small team and would genuinely appreciate your thoughts on this. Is this a problem you face? How would you improve this? Any and all feedback—positive or critical—would be incredibly helpful as we continue to build. PS - you can try it out from here: https://ift.tt/S0xEJTy August 27, 2025 at 10:21AM

Show HN: Smart Buildings Powered by SparkplugB, Aklivity Zilla, and Kafka https://ift.tt/HvQaZN9

Show HN: Smart Buildings Powered by SparkplugB, Aklivity Zilla, and Kafka https://ift.tt/CJ6xuyX August 29, 2025 at 03:03AM

Show HN: A private, flat monthly subscription for open-source LLMs https://ift.tt/q2m8hdw

Show HN: A private, flat monthly subscription for open-source LLMs Hey HN! We've run our privacy-focused open-source inference company for a while now, and we're launching a flat monthly subscription similar to Anthropic's. It should work with Cline, Roo, KiloCode, Aider, etc — any OpenAI-compatible API client should do. The rate limits at every tier are higher than the Claude rate limits, so even if you prefer using Claude it can be a helpful backup for when you're rate limited, for a pretty low price. Let me know if you have any feedback! https://ift.tt/PxrRW43 August 29, 2025 at 12:33AM

Show HN: Knowledgework – AI Extensions of Your Coworkers https://ift.tt/F6SPXoJ

Show HN: Knowledgework – AI Extensions of Your Coworkers Hey HN! We’re building Knowledgework.ai, which creates AI clones of your coworkers that actually know what they know. It's like having a version of each teammate that never sleeps, never judges you for asking "dumb" questions, and responds instantly. As a SWE at Amazon, I constantly faced two frustrations: 1. Getting interrupted on Slack all day with questions I'd already answered 2. Waiting hours (or days) for responses when I needed information from teammates When you compare this to the UX of an AI chatbot, humans start to look pretty inconvenient! It’s a bit of a wild take, but it’s really been reflected in my conversations with dozens of engineers, and especially juniors: people would rather spend 20 minutes wrestling with an unreliable AI than risk looking ignorant or wasting their coworkers’ time. One of my early users actually tried the product and told me she’s a bit worried her coworkers would prefer talking to her AI extension over talking to her! Here’s how it works: It’s a desktop app (mac only right now) that captures screenshots every 5 seconds while you work. It uses a bespoke, ultra-long context vision model (OCR isn’t enough, and generic models are far too expensive!) to understand what you're doing and automatically builds a searchable, hyperlinked knowledge base (wiki) of everything you work on - code you write, bugs you fix, decisions you make, or anything else you do on a computer that could be useful to you or your team’s productivity in the future. Even if you just turn on Knowledgework for ~30 mins while working on a personal project, I think you’ll find what it produces to be really interesting — something I’ve learned is that we tend to underestimate the extent of the valuable information we produce every day that is just ephemeral and forgotten. There’s also some really great opportunities surrounding quantified self and reflection — just ask it how you could have been more productive yesterday or how you could come across better in your meetings. The real value comes when your teammates can query your "Extension" - an AI agent that has access to all (only what you choose to share) of your captured work context. Imagine your coworker is on vacation, but you can still ask their Extension: "I'm trying to deploy a new Celery worker. It's gossiping but not receiving tasks. Have you seen this before?" We’ve spent a great deal of effort on optimizing for privacy as a priority; not just in terms of encryption and data security, but in terms of modulating what your Extension will divulge in a relationship appropriate way, and how you can configure this. By default, nothing is shared. In a team setting, you can choose to share your Extension with particular individuals. You can, in a fine-grained manner, grant and revoke access to portions of your time, or if you are on a tight-knit team, you can just leave it to AI to decide what makes sense to be accessed. This is the area we’re most excited to get feedback on, so we’re really aiming this launch at small, tight knit teams who care about speed and productivity at all costs who use Macs, Slack, Notion, and are all on Claude Code Max plans. We’re also working on SOC II type 2 compliance and can do on-prem, although on-prem will be quite expensive. If you’re curious about on-prem or additional certifications, I’d love to chat - griffin@knowledgework.ai. Check it out here: https://ift.tt/RQOltZ8 We’ve opened it up today for anyone to install and use for free. If you’re seeing this after Thursday 8/28, we’ll likely have put back the code wall — but we’d be happy to give codes to anyone who reaches out to griffin@knowledgework.ai https://ift.tt/RQOltZ8 August 29, 2025 at 12:11AM

Show HN: Persistent Mind Model (PMM) – Update: an model-agnostic "mind-layer" https://ift.tt/YEyz26K

Show HN: Persistent Mind Model (PMM) – Update: an model-agnostic "mind-layer" A few weeks ago I shared the Persistent Mind Model (PMM) — a Python framework for giving an AI assistant a durable identity and memory across sessions, devices, and even model back-ends. Since then, I’ve added some big updates: - DevTaskManager — PMM can now autonomously open, track, and close its own development tasks, with event-logged lifecycle (task_created, task_progress, task_closed). - BehaviorEngine hook — scans replies for artifacts (e.g. Done: lines, PR links, file references) and uto-generates evidence events; commitments now close with confidence thresholds instead of vibes. - Autonomy probes — new API endpoints (/autonomy/tasks, /autonomy/status) expose live metrics: open tasks, commitment close rates, reflection contract pass-rate, drift signals. - Slow-burn evolution — identity and personality traits evolve steadily through reflections and “drift,” rather than resetting each session. Why this matters: Most agent frameworks feel impressive for a single run but collapse without continuity. PMM is different: it keeps an append-only event chain (SQLite hash-chained), a JSON self-model, and evidence-gated commitments. That means it can persist identity and behavior across LLMs — swap OpenAI for a local Ollama model and the “mind” stays intact. In simple terms: PMM is an AI that remembers, stays consistent, and slowly develops a self-referential identity over time. Right now the evolution of it "identity" is slow, for stability and testing reasons, but it works. I’d love feedback on: What you’d want from an “AI mind-layer” like this. Whether the probes (metrics, pass-rate, evidence ratio) surface the right signals. How you’d imagine using something like this (personal assistant, embodied agent, research tool?). https://ift.tt/zchFrTO August 29, 2025 at 12:04AM

Show HN: Cross-device copy/paste and 5 MB file transfer (E2E, no signup) https://ift.tt/fRPgyNn

Show HN: Cross-device copy/paste and 5 MB file transfer (E2E, no signup) A browser-only way to copy/paste text and send small files between devices. • No accounts, join via code/QR • AES-256 E2E in the device • 5 MB file limit FAQ: https://ift.tt/bJ1Exfd https://ift.tt/9zKM5CE August 27, 2025 at 09:13PM

Show HN: Smooth – Faster, cheaper browser agent API https://ift.tt/RJHU2ZY

Show HN: Smooth – Faster, cheaper browser agent API Hey there HN! We're Antonio and Luca, and we're excited to introduce Smooth, a state-of-the-art browser agent that is 5x faster and 7x cheaper than Browser Use ( https://ift.tt/RzmvVfs ). We built Smooth because existing browser agents were slow, expensive, and unreliable. Even simple tasks could take minutes and cost dollars in API credits. We started as users of Browser Use, but the pain was obvious. So we built something better. Smooth is 5x faster, 7x cheaper, and more reliable. And along the way, we discovered two principles that make agents actually work. (1) Think like the LLM ( https://ift.tt/xj5I489 ). The most important thing is to put yourself in the shoes of the LLM. This is especially important when designing the context. How you present the problem to the LLM determines whether it succeeds or fails. Imagine playing chess with an LLM. You could represent the board in countless ways - image, markdown, JSON, etc. Which one you choose matters more than any other part of the system. Clean, intuitive context is everything. We call this LLM-Ex. (2) Let them write code ( https://ift.tt/UOVe1LA ) Tool calling is limited. If you want agents that can handle complex logic and manipulate objects reliably, you need code. Coding offers a richer, more composable action space. Suddenly, designing for the agent feels more like designing for a human developer, which makes everything simpler. By applying these two principles religiously, we realized you don't need huge models to get reliable results. Small, efficient models can get you higher reliability while also getting human-speed navigation and a huge cost reduction. How it works: 1. Extract: we look at the webpage and extract all relevant elements by looking at the rendered page. 2. Filter and Clean: then, we use some simple heuristics to clean up the webpage. If an element is not interactive, e.g. because a banner is covering it, we remove it. 3. Recursively separate sections: we use several heuristics to represent the webpage in a way that is both LLM-friendly and as similar as possible to how humans see it. We packaged Smooth in an easy API with instant browser spin-up, custom proxies, persistent sessions, and auto-CAPTCHA solvers. Our goal is to give you this infrastructure so that you can focus on what's important: building great apps for your users. Before we built this, Antonio was at Amazon, Luca was finishing a PhD at Oxford, and we've been obsessed with reliable AI agents for years. Now we know: if you want agents to work reliably, focus on the context. Try it for free at https://ift.tt/HBjTN3x Docs are here: https://ift.tt/DvjfBCY Demo video: https://youtu.be/18v65oORixQ We'd love feedback :) https://www.smooth.sh/ August 26, 2025 at 08:35PM

Show HN: Ubon – a solution for the "You're absolutely right" debugging dread https://ift.tt/nIziHo9

Show HN: Ubon – a solution for the "You're absolutely right" debugging dread I used Claude Code heavily while trying to launch an app while being quite sick and my mental focus was not at its best. So I relied 'too much' on Claude Code, and my Supabase keys slipped in a 'hidden' endpoint, causing some emails to be leaked. After some deep introspection, and thinking about the explosion of Lovable, Replit, Cursor, Claude Code vibe-coded apps, I thought about what's the newest newest and most dreadful pain points in the dev arena right now. And I came up with the scenario of debugging some non-obvious errors, where your AI of choice will reply "You're absolutely right! Let me fix that", but never nailing what's wrong in the codebase. So I built Ubon for the last week, listing thoroughly all the pain points I have experienced myself as a software engineer (mostly front-end) for 15 years. Ubon catches the stuff that slips past linters - hardcoded API keys, broken links, missing alt attributes, insecure cookies. The kind of issues that only blow up in production. And now I can use Ubon by adding it to my codebase ("npx ubon scan .", or simply telling Claude Code "install Ubon before commiting"), and it will give outputs that either a developer or an AI agent can read to pinpoint real issues, pinpointing the line and suggested fix. It's open-source, free to use, MIT licensed, and I won't abandon it after 7 days, haha. My hope is that it can become part of the workflow for AI agents or as a complement to linters like ESlint. It makes me happy to share that after some deep testing, it works pretty well. I have tried with dozens of buggy codebases, and also simulated faulty repos generated by Cursor, Windsurf, Lovable, etc. to use Ubon on top of them, and the results are very good. Would love feedback on what other checks would be useful. And if there's enough demand, I am happy to give online demos to get traction of users to enjoy Ubon. https://ift.tt/bleFB57 August 26, 2025 at 10:57PM

Show HN: Stop saving your scans on 3rd party servers https://ift.tt/CAHS6Qi

Show HN: Stop saving your scans on 3rd party servers Hi HN, I built DocsOrb to solve a simple but stressful problem (and my own problem too since many years!): keeping track of important documents like passports, rental contracts, and insurance papers. Too often they're scattered across folders, emails, or piles at home... and you only realize it when you urgently need them. DocsOrb helps you: > Scan documents with auto-crop and enhancements (mobile camera or file upload) > Organize them around life's "moments" (travel, housing, insurance, etc.) > Search quickly using Key Information > AI extracts Key Information so the most important details are always at your fingertips > Export or share in one tap > AI Bulk organize: load up multiple images from your Photos to automatically organize them as documents, put them in the right folders, extract Key Information and also suggest a recommended name and description. Everything stays on your device by default, with optional cloud backup if you want it. Privacy-first, so you're always in control. Tech-wise: it's built with Nuxt + Capacitor, Supabase for structured storage, and a custom scanning flow (to avoid pricey SDK lock-ins). I'd love your feedback: > Does this flow make sense to you? > What's missing in how you manage important documents? > Any suggestions before I go full blast on Marketing? https://docsorb.com/ August 26, 2025 at 06:06AM

Show HN: I built an AI trip planner https://ift.tt/hnqNSDj

Show HN: I built an AI trip planner https://milotrips.com August 26, 2025 at 02:39AM

Show HN: RAG-Guard: Zero-Trust Document AI https://ift.tt/cQVmwdM

Show HN: RAG-Guard: Zero-Trust Document AI Hey HN, I wanted to share something I’ve been working on: *RAG-Guard*, a document AI that’s all about privacy. It’s an experiment in combining Retrieval-Augmented Generation (RAG) with AI-powered question answering, but with a twist — your data stays yours . Here’s the idea: you can upload contracts, research papers, personal notes, or any other documents, and RAG-Guard processes everything locally in your browser. Nothing leaves your device unless you explicitly approve it. ### How It Works - * Zero-Trust by Design*: Every step happens in your browser until you say otherwise. - * Local Document Processing*: Files are parsed entirely on your device. - * Local Embeddings*: We use [all-MiniLM-L6-v2]( https://ift.tt/tN6WRkJ... ) via Transformers.js to generate embeddings right in your browser. - * Secure Storage*: Documents and embeddings are stored in your browser’s encrypted IndexedDB. - * Client-Side Search*: Vector similarity search happens locally, so you can find relevant chunks without sending anything to a server. - * Manual Approval*: Before anything is sent to an AI model, you get to review and approve the exact chunks of text. - * AI Calls*: Only the text you approve is sent to the language model (e.g., Ollama). No tracking. No analytics. No “training on your data.” ### Why I Built This I’ve been fascinated by the potential of RAG and AI-powered question answering, but I’ve always been uneasy about the privacy trade-offs. Most tools out there require you to upload sensitive documents to the cloud, where you lose control over what happens to your data. With RAG-Guard, I wanted to see if it was possible to build something useful without compromising privacy. The goal was to create a tool that respects your data and puts you in control. ### Who It’s For If you’re someone who works with sensitive documents — contracts, research, personal notes — and you want the power of AI without the risk of unauthorized access or misuse, this might be for you. ### What’s Next This is still an experiment, and I’d love to hear your thoughts. Is this something you’d use? What features would make it better? You can check it out here: [ https://mrorigo.github.io/rag-guard/ ] Looking forward to your feedback! https://ift.tt/D6mE35B August 26, 2025 at 03:12AM

Show HN: I built an image-based logical Sudoku Solver https://ift.tt/sna0DuP

Show HN: I built an image-based logical Sudoku Solver https://ift.tt/GnfUjlR August 26, 2025 at 12:09AM