how are you structuring your AI coding setup? (sharing mine, want to compare notes) been deep in the weeds optimizing my coding stack lately and want to see how you guys are actually running yours. here's where I'm at: what I pay for - Ollama - ChatGPT / Codex - Claude Code ($100 plan) how I split it - manual coding sessions → Claude Code - my orchestration layer (I call it Hermes) → runs on Codex with an Ollama fallback the issue: I cap out on the $100 Claude plan fast. so lately I've been running fcc-claude (free-claude-code) — it keeps the Claude Code terminal workflow but lets you point it at whatever API you want. feels like working in Opus, but the model underneath is swappable. I rotate the backend between: - DeepSeek - MiniMax M3 - and lately Qwen3:30b fully local right now I'm routing local Qwen through Ollama into fcc-claude, so I'm basically running the Claude Code experience on my own hardware for free. for the workflow layer I lean on Superpowers + a few MCP connections, and that's pretty much it. so what I'm trying to figure out: - how are you structuring sessions — one main agent, or orchestration with subagents? - what's your model routing look like? mixing local + API like this, or all-in on one provider? - what are you running for the "framework" layer — superpowers, custom skills, raw prompts? - and real talk: what am I missing? where am I leaving gains on the table? drop your setup below, even a rough sketch. trying to make sure I'm actually maxing this out and not just stacking tools for the sake of it.

Built by a developer who refused to run code he couldn't audit, the project strips OpenClaw down to ~500 lines handling everything. Agents execute inside Apple Container sandboxes (or Docker on Linux), with filesystem isolation enforced at the OS level rather than through application permissions. Setup happens through Claude Code itself - no installation wizard, no configuration files to learn, just run /setup and the AI handles dependencies, authentication, container configuration, and service deployment. Highlights: 1. Container-Level Security - Agents run in lightweight Linux VMs where only mounted directories are visible. Bash access is safe because commands execute inside the sandbox, not on your host. Mount allowlist validation sits at ~/.config/nanoclaw/ where agents can't reach it. 2. Skills-Based Customization - Contributors write skills like /add-telegram that teach Claude Code how to transform your fork. No PRs adding features to core—users run skills and get clean code matching their exact needs without bloat. 3. Memory Hierarchy - Global memory in groups/CLAUDE.md gets read by all conversations but only written by main channel, while each group maintains isolated memory in its own folder. Claude Agent SDK automatically loads both levels when agents run. 4. Scheduled Task System - Groups schedule recurring or one-time tasks that run as full agents with complete tool access, optionally messaging results back. Main channel manages all tasks across groups, others manage only their own. Nanoclaw is open source ❤️ Clone the repo, run Claude Code, execute /setup, and you have a working assistant. *Requires macOS or Linux and Claude Code installed.

chatGPT just released Sora2 an hour or two ago I think. If you are looking for invite codes some may be expired: A85AN6 ZNZ850 F2YNPB J7E9FJ Q89JFG KR76NK TR3B4C Have fun! Thanks https://www.skool.com/@endy-cheung-9935?g=ai-automation-society

Something pretty exciting just released from Google that I think you need to know about. They just released Genkit Go 1.0 - and before you think "oh great, another coding thing I can't use," hear me out. This could be the missing piece that takes your n8n automations from cool hobby projects to serious money-making businesses. What Is This Thing Anyway? Think of Genkit as a super-powered toolkit that makes building AI apps way easier. You know how n8n makes connecting different services simple with those drag-and-drop nodes? Genkit does something similar but for AI stuff - it connects different AI models (like ChatGPT, Google's Gemini, Claude) and makes them work together smoothly. The coolest part? It now has something called "AI-assisted development" where AI helpers can actually write code FOR you. Imagine having ChatGPT not just answer questions, but actually build entire applications based on what you describe. Why Should You Care as an n8n User? Here's the thing - you're already automating workflows and connecting APIs. You understand how powerful it is when different tools talk to each other. Genkit basically does that same magic but adds AI superpowers on top. For enhancing what you have now: - Your existing n8n workflows could trigger AI-powered analysis - Customer support bots could get way smarter - Data processing workflows could include AI insights - Content creation pipelines could become fully automated For building new businesses: - Custom AI tools for specific industries - AI-powered dashboards and reporting tools - Smart automation services for clients - AI consultants that work 24/7 The Business Opportunity Here Is Huge Think about it - most businesses are still figuring out how to use AI. They know they need it, but they don't know how to build it or make it work with their existing systems. That's where you come in. You already understand automation and workflow design. Now imagine being able to offer clients: - Custom AI chatbots that actually understand their business