Supabase’s Plan for a Billion AI-Built Apps
Supabase’s Plan for a Billion AI-Built Apps
Supabase plans to run long-running workloads alongside its database using Supabase Compute, simplify schemas to make them easier for AI agents to understand, and design infrastructure that supports more applications. Its acquired Turso product supports scaling, and the company is using AI internally to improve efficiency while maintaining a parallel approach of open-source and commercial sales.
AI agents are creating more software—and that changes what a backend needs to do. Supabase co-founders Paul Copplestone and Ant Wilson join swyx to discuss running long-lived workloads alongside the database, making schemas easier for agents to understand, and designing infrastructure for a world with many more applications.
The conversation also covers Postgres reliability and scaling, Turso, open source, community-led distribution, and how Supabase uses AI internally. Recorded ahead of Supabase Select 2026.
Show notes
Supabase Compute — run workloads alongside the database.
Multigres — highly available Postgres infrastructure, in private alpha.
Supabase acquires Turso — the scale-out opportunity.
Supabase Select — the event discussed in the interview.
Chapters
00:00 Six years in the making
00:51 Supabase Compute
02:01 OrioleDB and the Postgres storage engine
03:27 Multigres and Postgres reliability
07:06 Scaling out and Turso
23:10 From prototype to petabyte
25:10 AI and Supabase’s growth
27:40 Agent-driven activation
30:00 Community and crowdfunding
36:00 Open source and enterprise sales
40:50 Will the application builder or database be stickier?
48:10 Durable workflows
50:52 Company priorities
53:24 Code-first infrastructure and declarative schemas
56:30 Will AI-generated software converge?
1:06:01 How Supabase teams use AI
1:09:45 Hiring for a remote-first company
Source: Latent Space · latent.space