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Friday, August 29, 2025
Show HN: Knowledgework – AI Extensions of Your Coworkers https://ift.tt/rqyTwz9
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/MEcmDWs 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/MEcmDWs August 29, 2025 at 12:11AM
Thursday, August 28, 2025
Show HN: Chat with Nano Banana Directly from WhatsApp https://ift.tt/3stS1lM
Show HN: Chat with Nano Banana Directly from WhatsApp Hey everyone, built this earlier today on my whatsapp no code platform - been going a bit viral between my social groups so thought I'd share with you guys :) https://ift.tt/wIE0gxz August 27, 2025 at 10:43PM
Show HN: AIMless (Live Demo) P2P Encrypted Chat in One HTML File https://ift.tt/3LTES6O
Show HN: AIMless (Live Demo) P2P Encrypted Chat in One HTML File Last week I shared the repo for AIMless, my silly experiment to see how far I could push “chat app, but only index.html.” Now it’s live at https://aimless.chat so you don’t even have to clone or double click anything. just open and relive your AIM nostalgia. INSTRUCTIONS: Host clicks “Create” → gets a blob. Copy/paste blob to your friend. Friend pastes, returns blob. Boom, encrypted chat like it’s middle school and your mom needs the phone line. Github: https://ift.tt/1MpzBPe https://aimless.chat/ August 27, 2025 at 10:18PM
Show HN: Cross-device copy/paste and 5 MB file transfer (E2E, no signup) https://ift.tt/5UBECFw
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/mkH7D1L https://ift.tt/yzUtGfx August 27, 2025 at 09:13PM
Wednesday, August 27, 2025
Show HN: Smooth – Faster, cheaper browser agent API https://ift.tt/5NerRSZ
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/yKQnk8l ). 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/SUL1H9F ). 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/IcEBKML ) 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/fyXpOvh Docs are here: https://ift.tt/78GJ6qf Demo video: https://youtu.be/18v65oORixQ We'd love feedback :) https://www.smooth.sh/ August 26, 2025 at 08:35PM
Show HN: Enterprise MCP Bridge – Solving the MCP Chaos for IT https://ift.tt/Dd8wzl1
Show HN: Enterprise MCP Bridge – Solving the MCP Chaos for IT Working in IT at a company with a change management process? How are you handling MCPs? Not at all? With very expensive tools not up to the task? How about just making it fit into your current setup! We needed to build this for inxm.ai, and realised this was the perfect time to give back to the community. Enterprise MCP Bridge is Open Source and solves Auth, Multi User, and REST apis by wrapping your existing MCPs. https://ift.tt/xQfzryF August 26, 2025 at 11:21PM
Show HN: Ubon – a solution for the "You're absolutely right" debugging dread https://ift.tt/G45qWkh
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/Rv0NfQ5 August 26, 2025 at 10:57PM
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Show HN: Carrie, for what Calendly can't do https://ift.tt/jz98xi4
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Show HN: Snap Scope – Visualize Lens Focal Length Distribution from EXIF Data https://ift.tt/yrqHZtDShow HN: Snap Scope – Visualize Lens Focal Length Distribution from EXIF Data Hey HN, I built this tool because I wanted to understand which...