Madison Faulkner is Head of Strategic Initiatives at Factory and a venture advisor at New Enterprise Associates, working on how autonomous coding agents reshape software development and its underlying infrastructure. She joined Factory after backing the company as an investor and serving on its board.
Faulkner studied management science and engineering at Stanford and worked in data science at Facebook, including advertising auctions and research with Facebook AI Research. She subsequently led data science at Greycroft and data science and machine learning at Thrasio before becoming a vice president at Costanoa Ventures. She joined NEA in 2024 to invest in early-stage data infrastructure, developer tools, and artificial intelligence; the firm promoted her to partner in 2025.
At NEA, Faulkner helped articulate the investment case for Factory, whose software agents, called Droids, operate across the development lifecycle. NEA led Factory’s $50 million Series B, and Faulkner served on its board before joining the company to lead strategic initiatives. She remains affiliated with NEA as a venture advisor.
- Agent-native software development: Coding agents become more useful when they understand repositories and organizational context, coordinate specialized work, and handle testing, migrations, review, and feature development throughout existing enterprise workflows.
- Enterprise code modernization: Faulkner emphasizes the difficulty of improving large production systems, where repository context, recurring migrations, end-to-end validation, and accumulated context debt matter more than isolated code-generation benchmarks.
- Continuous compute for coding agents: Autonomous agents can overwhelm human-paced CI/CD with simultaneous branches, builds, tests, and pull requests. Faulkner advocates faster execution over existing infrastructure, stronger caching and orchestration, ingress shaping, rate limiting, agent identity, and reliable retries—an argument developed in her work on Namespace and AI Engineer Europe appearance.
- AI-native analytics architecture: Her investment thesis on Golden Analytics argues that enterprise analytics should let AI work directly with data and guide users toward reliable analysis, instead of layering conversational interfaces over fragmented business-intelligence systems.
