Addrly
A utility hub for founders building and scaling B2B products
What it does
Addrly is a utility-first resource hub built for founders who want practical answers without digging through endless articles, frameworks, and spreadsheets. It brings together API protocols, strategic playbooks, diagnostic calculators, and other useful resources for building and scaling B2B products. What started as a hobby project and personal experiment is now a small collection of tools designed around one principle: less fluff, more utility.
Browse information-dense, step-by-step API integration guides for your entire B2B SaaS stack. Connect CRMs, ERPs, marketing suites, and more — zero fluff, pure utility.
Stop scavenging for tactical advice. Access a curated repository of API protocols, strategic playbooks, and operational blueprints. Verified, information-dense, and built for speed. A definitive guide for CEOs on the difference between cheap AI 'wrappers' and true, proprietary enterprise AI integrations. Learn how to build a real AI moat. A comprehensive executive guide on the true cost of off-the-shelf SaaS versus custom enterprise software. Learn when to buy and when to build with Upturne. Discover the hidden challenges of maintaining and scaling a startup. Learn why technical debt and fragile infrastructure are the silent killers of growing companies. A definitive guide for founders on…from addrly.in
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 26d ago · cactuscompute.com
Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com