Shawn Wang

Paul Copplestone says Supabase does not set one AI coding policy for the whole company. Product teams already choose their own tools and habits, and coding agents were left the same way. A few cost rules are starting to line up. He still wants each team to decide.

Shawn Wang asks how much the company spends and whether the bill is a worry. Copplestone answers with who decides, not with a company-wide cap. Because the company is remote, decisions are written down, so he can ask an assistant what the bill is. The figure he gives is about $300,000 a month for about 450 people. He first says 600 and corrects it to 450. Hiring is fast, so the bill moves with headcount when the tools give the tea

Paul Copplestone says a database is harder to leave than a frontend tool, which is why Supabase can stay stickier than a coding app such as Lovable. Shawn Wang had asked whether a product chief ends up more attached to the coding app or to the database. Lovable was also the first of the coding apps to stop its agent from doing damage.

Early agents stuffed image data into Postgres and turned off row-level security just to make a project run. Lovable wrote skills that blocked the moves. He treats the restraint as the useful part. Newer models have stopped making the same mistakes on their own, so the failure is less common than it was.

Shawn Wang says his tracking of model answers shows frontier models recommending Supabase as the default integrated backend: the database, auth, functions, and the other APIs in one place. He traces the lead to being in the market for three or four years before the models took off, already the open-source alternative people compared with Firebase.

Paul Copplestone calls the timing an accident and says the job now is to keep the lead. The early habit of spending time with the community left posts, videos, and podcasts about how to build on Supabase, and open source made that material easy for a model to read.

Paul Copplestone says the latest jump in Supabase signups came from the models getting better, not from a marketing spend. Most of what they spend on attention is still memes.

A flood of lighter traffic usually hurts activation and the share of people who start paying. Both went up. The agent finishes signup and activation in one step, so activation is almost 100 percent. The new users also started paying at a higher rate than developers who signed up the old way.

Shawn Wang pulls up the signup chart and says the curve keeps forcing a new axis. The unusual part, in Copplestone's account, is that activation and payment rose together as the audience got broader. Friction at the front door wa

Shawn Wang says Paul Copplestone and Ant Wilson, the Supabase co-founders, went through Entrepreneur First in Singapore, each on a different company, and stayed after the cohort as housemates.

Paul Copplestone says seven people lived in one house, each running a different startup, before Supabase. An accelerator usually pairs a technical founder with a domain expert. Everyone in the house was a builder. Pairing two builders got more done on developer tools, because a developer is already the subject-matter expert. The co-founders kept building together from there, and they hired most of the other people who had lived in the house. Rory, one of them, went on to run go-to-market.

Katelyn Lesse says an agent's hands should only reach the network places the setup allows. Untrusted code can run in the sandbox, and egress can be an allow list or shut off entirely.

Claude Managed Agents ship that architecture out of the box. As the platform team learns a new control, customers get it without rebuilding the harness. She groups the new vocabulary as brain and hands, credentials, injection, and egress. Nine months earlier, nobody was using those words. They are new problems, and the team wants customers to pick up the fixes while Anthropic is still solving them in its own infrastructure. Internally, the same systems are being moved to secure by default.

She agrees that clo

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