I ran a benchmark that surprised me. Same AI. Same prompt. Two different approaches to building n8n workflows. Here's what happened: n8n MCP / Skills: ⏱ 15+ minutes to generate 🔴 Hit context limits mid-way ❌ Unconnected nodes, validation errors — unusable out of the box n8n-as-code: ⚡ ~3 minutes 🟢 Low token usage ✅ 100% valid, pushed live with no errors The reason isn't the AI — it's the architecture. MCP dynamically fetches node schemas on every call. Constant roundtrips, massive context pollution, and the AI still guesses wrong half the time. n8n-as-code maps the entire n8n node structure as TypeScript in your IDE. Your AI agent has perfect context locally — before it writes a single line. When to use which: → n8n MCP — Quick exploration, simple workflows, no IDE setup needed → n8n-as-code — Complex workflows, team projects, GitOps, production-ready automations Reliable automation isn't about more nodes. It's about tooling that doesn't hallucinate them. Has anyone else here made this switch? Would love to hear what workflows you're building with it.

built a chrome extension that reads the job post and based on job role, experience, education, and master resume creates a shorter and more fitting resume with the keywords and phrases an employer will look for when reviewing your resume. This saves you tons of time and increases your odds of getting you an interview and thus the J O B.

Hello, I work in tech and have a strong interest in AI, thought the community looked interesting! Excited to learn new things.