Creator & CEO |Pydantic
Created Pydantic (most used Python validation library) and Pydantic AI, bringing FastAPI-like ergonomics to agents.
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key/value store for Python based on Cloudflare workers
PWA to show a QR code with your email address.
plot data from a parquet file
CLI for tinifying images and checking they're tinified.
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Biography
Samuel Colvin is a Python and Rust developer and the Founder & CEO of Pydantic, a Sequoia-backed company building the data validation and AI agent infrastructure used by millions of developers. He started Pydantic in 2017 out of frustration that Python type hints did nothing at runtime, and curiosity about whether they could be used to validate data. What began as a side project is now downloaded over 300 million times per month and has surpassed 10 billion total downloads. Colvin holds an MEng in Mechanics and Fluid Dynamics from the University of Cambridge (2006-2010). Before Pydantic, he was Director and CEO of TutorCruncher. In 2023 he raised $4.7M seed from Sequoia, and in 2024 closed a $12.5M Series A to launch Pydantic Logfire (an observability platform) and Pydantic AI (an agent framework that became the fastest-growing agent framework by downloads in 2025). He is based in London, UK.
The most widely used data validation library in Python, with 300M+ monthly downloads. Pioneered using type hints for runtime validation.
Rust-based validation core powering Pydantic v2, delivering 5-50x performance improvements over the pure-Python v1.
Type-safe AI agent framework bringing FastAPI-like ergonomics to LLM agents. Fastest-growing agent framework by downloads in 2025 (8M/month).
AI observability platform for production LLM and agent systems, providing tracing, monitoring and debugging.
Fast, iterable JSON parser written in Rust, used as the JSON parsing backend in Pydantic.
Framework for building web UIs defined by Python code, using Pydantic models for the component schema.
Annual fund investing $2,000+ per developer per year back into the open source ecosystem (currently $30k/year across 14 developers).
Back in 2017, when I first started it, the different thing it was doing was using type hints to define your schema. That was controversial at the time... today that's no longer controversial in Python.
Pydantic today is downloaded 300 million times a month. It's important to remember we're talking about GenAI today, but one of the powers of Pydantic is it is not just for GenAI.
For LLM agents to be reliable, they need a clear understanding of the tools they can access and the data they can expect — that's where Pydantic's principles of type safety become crucial.
Research generated March 19, 2026