Ian Webster is the co-founder and chief executive of Promptfoo, the open-source AI security and evaluation company now part of OpenAI. He builds tools that help developers identify dangerous behavior in language-model applications before those systems reach customers or gain access to sensitive information.
Webster previously held engineering roles at Room 77 and Google and created Asterank, a database for visualizing and assessing asteroids that Planetary Resources acquired in 2013. Its visualization technology later informed SpaceKit, an interactive space-visualization library. His other projects include Ancient Earth, which maps the planet’s geological history. He also co-founded Zenysis, serving as chief technology officer of a company building data-integration software for governments confronting public-health emergencies and humanitarian crises.
At Discord, Webster founded and led developer-platform and developer-relations teams before helping build Clyde, the company’s conversational AI assistant. Deploying an AI product at consumer-platform scale made safety, privacy, legal exposure, and adversarial misuse immediate engineering problems. Webster began developing Promptfoo’s open-source evaluation framework during that work; its first public release arrived in 2023, and he founded the company with Michael D’Angelo in 2024.
Promptfoo raised a $5 million seed round in 2024 and an $18.4 million Series A in 2025. When Webster and D’Angelo announced that Promptfoo would join OpenAI in March 2026, they reported more than 350,000 developers had used the platform. Its open-source tools are expected to contribute to OpenAI Frontier’s enterprise security and evaluation capabilities.
- Developer-first evaluation: AI evaluations should behave like software tests: local, fast, understandable, and integrated into pull requests. Webster favors targeted deterministic checks, including testing whether informal chatbot responses begin with lowercase letters and assessing retrieval triggers separately from summarization.
- Application-specific red teaming: Safe base models can become vulnerable once developers add system prompts, retrieved documents, tools, or external integrations. Webster tests complete applications for jailbreaks, harmful outputs, sensitive-data leakage, and unintended actions before deployment.
- Model-specific prompt design: Accumulating special-case instructions can degrade performance, and prompts tuned for one model family may fail on another. Webster advocates simpler prompts and fresh evaluation when changing providers.
- Privacy-aware production feedback: At Discord, his teams built evaluation cases from internal testing and public reports without recycling private conversations, kept prompts in Git, and reused existing observability infrastructure. They also experimented with occasional stronger-model responses to correct conversational personality drift.
