... local repository is rarely just source code. Over time, it becomes a mix of source files, Git history, dependencies, generated build output, caches, logs, assets, local databases, framework artifacts, and tool-specific folders. That makes project size surprisingly hard to reason about. When a repo grows to 10 GB, 30 GB, or more, the first question should not be: What can I delete? It should be: What is this project actually made of? That idea became Projects in Room Service ... ... data, dependencies, build outputs, caches, assets, logs, and source files, so developers can understand project structure before making cleanup decisions. This becomes especially useful in monorepos, long-running client projects, game development folders, and AI-heavy environments where generated artifacts

... makes pricing easier. Products from anonymous creators compete on price. Products from known practitioners with a track record compete on trust. That's a completely different conversation. Comment from Samir Asadov(@samir_asadov): For specialist/practitioner products this 'brand vs product' framing breaks down the product IS the brand statement. A financial model template built from real deal experience signals more credibility than a thousand brand posts ever could, because the buyer (a CFA with a deal on their desk) reads ... ... structure, assumption choices, and waterfall logic the way a developer reads source code. They can tell in 90 seconds whether the author has actually sat in the same chair. What does compound: credentials + shipped artifacts

... months, I ve been analyzing how AI answer engines discover and interpret websites. We re starting to see a pattern: robots.txt controls crawling sitemap.xml helps discovery structured data helps search engines But AI systems introduce something new: AI-ready artifacts like: ai.txt llms.txt ai-feed.json structured RAG indices Some companies are already publishing these. Most are not. My questions to builders and founders here: Are you exposing structured artifacts

... companies know how they re being cited, summarized, or interpreted by AI systems? SEO tools measure rankings. Analytics tools measure clicks. But AI answer engines introduce a new layer: Are you cited? Which sources are used? Are structured artifacts discoverable? Is your brand being summarized accurately? I ve been building infrastructure to analyze this (AI-ready artifacts

... Gemini, Copilot, Claude, Perplexity, and other AI systems. I m the Founder of NeuralBubble the Global AI Visibility Engine. At NeuralBubble, we built an AI Visibility Infrastructure platform focused on GEO (Generative Engine Optimization). Our system analyzes AI-ready artifacts, structured signals, and citation patterns using proprietary indices the GEO Readiness Index (GRI) and Artifact

... Shotgun - to help you turn technical research and spec generation into context for software engineers, AI code-gen tools like Codex, Cursor, Claude Code, with complete codebase understanding, and agents doing the heavy lifting. Shotgun produces clean, reusable artifacts and exports to the agents.md ecosystem to help you get the most out of code-gen tools and Agents. New release highlights: : Modes: Research Specify Plan Tasks Implement Hit Shift+Tab to summon different expert advisors for each stage. Researcher, spec ... ... writer, architect, task planner all at your service. Switch freely. Shotgun adapts to you, not the other way around. Export to agents.md Every artifact

... quality footage, whether it s from old phones, webcams, screen recordings, or even modern cameras shooting in low light or tough conditions. You can 2x or 4x upscale while keeping things looking natural - no waxy faces, no over-sharpened artifacts. We re not claiming to be the best (yet), but we re working toward it with every update. Thank you for your support ...