February 13, 2026 Read on ssp.sh
4.5

Building an Obsidian RAG with DuckDB and MotherDuck

Data EngineeringTools & ProductsAI & LLMsWriting & LearningIndustry

Simon Späti built a personal knowledge assistant using RAG on his Obsidian vault, with DuckDB as the vector database locally and MotherDuck for a serverless web app via WASM. The system uses BGE-M3 embeddings to enable semantic search across nearly 9,000 markdown notes, leveraging Obsidian's backlink graph to boost results and surface hidden connections between notes. He emphasizes the local-first approach to keep sensitive notes private. The article doubles as a reflection on AI agents in data engineering, arguing that 'plan mode' in tools like Claude Code is the real productivity breakthrough — not smarter models. He cautions that vibe coding and AI agents still require a human architect to avoid generating unmaintainable code that solves the wrong problem.

AI agents accelerate building but the real productivity unlock is plan mode — structured human-in-the-loop planning before autonomous execution — not smarter models.
  • 3

    I was surprised how well DuckDB handles this without a dedicated vector database, one file for relational data and vectors together.

  • 4

    The hidden connections this tool surfaces are valuable only because they're my connections, my thinking, not just crawled information on the internet.

  • 6

    Let them run without direction, and you'll get a thousand lines solving the wrong problem.

  • 4

    I get the perception of being super productive, but after a couple of hours, or sometimes days, we actually didn't achieve what we needed.

  • 5

    The character and soul of the person gets stripped away. The quirky things someone does, which make them who they are, that takes away from the fun of writing.

  • 5

    Always keep it simple, because it's easy to make it complex. The true beauty lies in making it simple, which is something agents are not good at.

  • 4

    Human in the seat and config-driven development is what it comes down to with AI agents.

  • 5

    The hard part is coming up with the spec, talking to business, etc. The coding part is the small part.

practical, reflective, opinionated