Understanding Tokens in Language Models

It’s always a good day if you see a pelican. In Episode 30 of Talking Postgres with Claire Giordano, open source developer Simon Willison—creator of Datasette and co-creator of Django—joins to explore how AI is useful for data engineers today. We move past the hype and boosterism to dig into example after example: structured data extraction, alt text and accessibility, safety and security (aka the fiddly bits), and why Postgres’s fine-grained permissions are such a good fit for AI-powered workflows. Also: Pulitzer-worthy data tooling, the science fiction of the 10X engineer, agents, MCP, RAG, the multitude of models, and why Simon spends so many waking hours on the jagged frontier of AI.

Links mentioned in this episode:

• Blog: Simon Willison’s Weblog
• Blog: Simon’s Willison’s TIL - Things I’ve Learned
• Podcast episode: Working in public on open source with Simon Willison and Marco Slot
• Project page: Django Web Framework
• Project page: Datasette, for finding stories in data 
• GitHub repo: llm CLI tool and Python library
• Demo: Language models on the command-line w/ Simon Willison
• Blog post: OpenAI’s new open weight (Apache 2) models are really good, by Simon Willison 
• Podcast episode: Accessibility and Gen AI podcast with guest Simon Willison
• Blog post: New dashboard: alt text for all my images, by Simon Willison 
• Keynote talk: Big Opportunities in Small Data, by Simon Willison at Citus Con: An Event for Postgres 2023 
• Blog post: How OpenElections Uses LLMs, by Derek Willis 
• Blog posts tagged with pelican-riding-a-bicycle on Simon Willison’s Weblog 
• Blog post: No, AI is not Making Engineers 10x as Productive, via Colton Voege, featured on Simon’s weblog
• GitHub repo: pgvector extension to Postgres
• Cal invite: LIVE recording of Ep31 of Talking Postgres to happen on Wed Sep 17, 2025