

Sam Bhagwat
Co-founder and CEO of Mastra and former co-founder of Gatsby; author of Principles of Building AI Agents and experienced in developer tools and frontend engineering.
Top 3 podcasts with Sam Bhagwat
Ranked by the Snipd community

97 snips
Oct 30, 2025 • 57min
Building AI Agents on the Frontend with Sam Bhagwat and Abhi Aiyer
Sam Bhagwat, Co-founder and CEO of Mastra, and Abhi Aiyer, Co-founder and CTO, dive deep into the world of AI agents designed for frontend developers. They tackle the challenges of building full-stack AI applications using TypeScript, highlighting Mastra's tools and workflows. They discuss unique use cases, such as CAD generation and industry-specific vertical agents. With insights on developer experience and a roadmap for future features, they offer practical advice for aspiring AI engineers eager to innovate in this rapidly evolving space.

16 snips
Jul 24, 2025 • 47min
Sam Bhagwat from Mastra: the Gatsby founder building an agents framework
Sam Bhagwat, CEO of Mastra and co-founder of Gatsby, discusses his journey in building AI frameworks. He reveals why they chose TypeScript over Python and the surprising engagement from Japanese developers. Sam shares insights on localizing resources and the impact of community feedback on product evolution. They also delve into the significance of high-quality documentation in user experience, and the distribution of 1,500 physical books a week to bridge knowledge gaps in AI development.

11 snips
Dec 2, 2025 • 38min
Principles of Building AI Agents (ft Sam Bhagwat)
Sam Bhagwat, founder of Mastra and co-founder of Gatsby, sheds light on crafting effective AI agents. He discusses the advantages of using TypeScript for agent frameworks and highlights crucial design patterns for tools and prompts. Sam emphasizes the importance of memory types, including observational memory, and warns about the 'lethal trifecta' in security risks. He also shares insights into multi-agent communication and operational safety, aiming to demystify the complexities of building reliable AI agents.


