MOOC completion rates hover at just 5–15%, and the problem isn't course quality — it's the execution gap. DaoDao positions itself as a 'Learning OS,' using public commitments, community interaction, and AI recommendations to make learning visible and sustainable.
DaoDao is not a content platform -- it's a learning connector. Using anti-perfectionism design, community co-learning, and zero-decision recommendations, it helps learners bridge the execution gap -- from vague ideas to actionable plans.
NobodyClimb uses RAG to tackle scattered climbing route information, ties quota limits to community engagement, and leverages Cloudflare Workers AI to bring inference costs close to zero.
To consolidate scattered notes and showcase diverse interests, I built a personal blog using Astro + Cloudflare Workers D1, paired with a Claude post skill for zero-friction writing.
Next.js + Expo frontend, Node.js + Python dual backend, PostgreSQL + Redis core — plus a social notification system and LLM recommendation engine. Here's how DaoDao builds a learning community platform with a modern tech stack.
A dynamically composable RAG pipeline built on Cloudflare Workers AI (gemma-3-12b-it + bge-m3): 14 base steps + 6 LangGraph-specific nodes, with three strategy graphs (Baseline / Agentic / Plan-Execute) selected at runtime.
Switching templates means replacing the entire project foundation. Figure out what you actually need first, then choose between AstroPaper, Cactus, or AstroWind.