# LanceDB Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/lancedb
> Markdown URL: https://aitinkerers.org/technologies/lancedb.md
> Technology record last updated: 2026-02-25T04:45:05Z
> Generated: 2026-09-21T21:38:25Z

LanceDB is the serverless, open-source vector database for multimodal AI: it powers fast, scalable RAG and semantic search applications.

LanceDB is your multimodal AI lakehouse, built on the high-performance Lance columnar format (Rust-based). This architecture provides a unified data store, natively handling vectors, metadata, and raw multimodal data (text, images, video) to eliminate separate databases. Leverage its disk-based indexes for low-latency vector search, full-text search, and SQL queries over petabyte-scale datasets. The platform delivers the speed and scalability required for production-ready RAG, autonomous agents, and large-scale model training workflows.

- Official technology site: https://lancedb.com/
- Public AI Tinkerers demos and talks: 5
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Agents Building Agents: Reflective Optimization Loops](https://toronto.aitinkerers.org/talks/rsvp_4gS7qartFFk)

I'll show how an AI agent can build and optimize another AI agent, using reflective optimization to find issues, optimize evals, iterate on architecture, find the optimal prompt/model, and more. We've built a system with multiple levels of reflective optimization for agent development. - GEPA: reflective prompt optimization - Synthetic eval generation: going from a 1-off bug to an proper eval you can use in reflective optimization - Expanding reflective optimization beyond prompts: model selection, tool use, subagents -- reflective optimization can drive all levels of agent optimization.

- Event context: AI Tinkerers Toronto - April 2026 - hosted by Shopify — 2026-04-29 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_4gS7qartFFk

### [Reality Check: Building a Personal Fact-Checking Framework](https://tokyo.aitinkerers.org/talks/rsvp__DhnH1LfZlw)

Hot takes. Plausible theories. AI-generated slop. LLM psychosis. How do you keep track of what's actually true? Reality Check is an open-source framework for building a personal fact-checking knowledge base—using Agentic tools (Claude Code, Codex, etc) to track claims, sources, predictions, and argument chains with a LanceDB-backed semantic search. I'll show how the system extracts claims from articles, assigns evidence levels and credence scores, and generates analyses, but also how I went about building it, from an initial prototype to several refactors over the course of a few days.

- Event context: AI Tinkerers Tokyo - Toranomon Meetup - February 19, 2026 — 2026-02-19 — Tokyo
- Public talk page: https://tokyo.aitinkerers.org/talks/rsvp__DhnH1LfZlw

### [Archetype - A Novel Entity-Component-System for AI-Driven Simulations](https://chicago.aitinkerers.org/talks/rsvp_0SUlhpOnBSw)

I’ll present Archetype, an Entity-Component-System (ECS) framework built for AI-driven simulations. I’ll showcase live code in VS Code, demonstrating how Archetype manages entity state across multiple simulations using a custom data store. You’ll see how it handles dynamic entity creation, state querying, and data persistence at scale, with a focus on the core storage module that leverages columnar data formats for performance. I’ll also walk through a practical example of simulating entities with diverse behaviors, highlighting the technical implementation details and challenges overcome during development.

- Event context: AI Tinkerers Chicago June Meetup ft Bonsai — 2025-06-03 — Chicago
- Public talk page: https://chicago.aitinkerers.org/talks/rsvp_0SUlhpOnBSw

### [Tactician: Detailed, specific workplace advice for confusing or political situations](https://seattle.aitinkerers.org/talks/rsvp_gumR4iFgXLM)

I'm baking everything I learned through my PhD in Organizational Behavior and my years as a professor in the field, combined with my lifelong interest in organizational effectiveness, into Tactician. Tactician isn't a single advice-bot. It's a system that combines distinctly different perspectives, careful questioning and hypothesis-testing, and freeform chat to get you evidence-based, actionable advice. In the live demo I'll walk through a real workpalce scenario (people come to me for advice with these all the time). We'll chat with the advisor personas first. Then we'll give some further tailored details, based on an intake survey that's dynamically generated based on the chat. We'll see the combination of these piped back to the advisors, who will suggest little hypothesis tests in the real world so you can figure out what is actually going on. We'll simulate this in the demo. Once we're sure of the facts, the advisors present courses of action that seem likely to lead to a integrated good outcome: something that will be beneficial both for you and the organization. It's a system based on careful data selection, an agentic workflow (BAML, pydantic), RAG from a vector db with only the choicest organizational texts in it, and (eventually) fully local and private models to offer a complete tailored advice system. Starting by hooking it up to Claude 3.7 sonnet with some prompt engineering for multiple advice personas. Use-case spiel: Maybe you interacted with a boss or client recently who said something confusing but important. Maybe you're in a situation where people expect you to have a lot of people skills and you feel overwhelmed. Use Tactician to figure out a) what's going on, b) what your options are to get to a good outcome.

- Event context: AI Tinkerers Seattle - April Meetup — 2025-04-25 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_gumR4iFgXLM

### [Open source data ingestion for RAGs](https://berlin.aitinkerers.org/talks/rsvp_-LOBg49gB3I)

A demo of how to use dlt, an open source data ingestion tool, to pull data from a REST API with minimal code and load it into LanceDB, an open source vector DB that stores both your data and its embeddings. This addresses challenges around keeping RAGs up to date and minimizing database maintenance.

- Event context: Ollama & Friends coming to AI Tinkerers Berlin — 2024-07-18 — Berlin
- Public talk page: https://berlin.aitinkerers.org/talks/rsvp_-LOBg49gB3I

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