Deployed: The AI Product Podcast

On this episode of Deployed, we sit down with Shuhao Zhang, co-founder and CPO of TinyFish, on launch day for Mino (mino.ai) - an enterprise web agent platform that handles reasoning, multi-step execution, and parallel browser sessions at scale.Shuhao shares his vision for the "operational web" where AI agents become the primary operators of the web, unlimited by human constraints. He shares a live demo and customer stories, like working with Google to connect tens of thousands of Japanese hotels to consumers, and with ClassPass to maintain up-to-date pricing across 30,000 wellness studios.Key technical insights for builders include:- Why public benchmarks for web agents are saturated today, and you need your own evals- How they built infrastructure to replay sessions like a "time machine" for data iteration- Why they fix issues through data improvement rather than custom patches / rule-based systemsLearn more:- Minnow: mino.ai- Tiny Fish: tinyfish.ai- AgentQL: agentql.com- Find Shuhao on LinkedIn (https://www.linkedin.com/in/shuhao/) and Twitter (https://x.com/shuhao_friday)

On this episode of Deployed, we sit down with Ajit Varma, VP of Product at Mozilla Firefox, and former product leader at Google, Meta, Square, and WhatsApp. Ajit brings a unique perspective: while venture-backed AI browsers race to build what increasingly look like walled gardens, Mozilla has spent months quietly shipping privacy-first AI features that put user choice above everything else.It's a thoughtful conversation with candid insights into why Firefox offers multiple AI chat providers in their sidebar instead of forcing users into a single model (and how this philosophical stance shapes every technical decision they make), the reality that privacy-preserving AI requires completely rethinking architecture, and why their AI features prioritize on-device processing whenever possible. We also get into the technical challenges that come with balancing local and cloud AI (users want SOTA quality but also want their data to stay private), the business model constraints of being a nonprofit foundation competing against VC-funded competitors who can burn cash on flashy features, and why Mozilla believes keeping the web open matters more than winning the AI browser wars. Whether you're interested in privacy and the open web or just trying to understand what it takes to integrate cutting-edge AI into existing products, Ajit's perspective offers practical lessons from someone navigating a challenging balancing act.

On this episode of Deployed, we sit down with Surojit Chatterjee, CEO and founder of Ema, and former VP of Product at Google and Chief Product Officer at Coinbase. Surojit brings a rare perspective: he started building enterprise AI agents in early 2023—well before "agentic AI" became a buzzword- and has spent two years getting them to production quality that companies like Hitachi actually trust. Surojit gives us refreshingly candid insights into why Ema calls their products "AI Employees" instead of agents (and how this completely changes their approach to feedback and evaluation), the reality that most enterprise AI projects fail because companies try to automate broken processes instead of redesigning them, and why multi-agent systems are essential for handling real enterprise complexity. We dive into the technical challenges that remain unsolved (complex dynamic planning with long tool chains is still hard), his forward-deployed "agentic clinics" approach to customer success, and why sustainable scale matters more than flashy demos. Whether you're building AI products for the enterprise or trying to understand what it really takes to transform critical business processes with AI, Surojit's battle-tested perspective offers practical lessons from someone who's been in the trenches longer than most.

In this episode of Deployed, we sit down with Ryan Carson, Builder in Residence at Amp (Sourcegraph's coding agent) and founder of Treehouse, which taught over a million people to code. Ryan brings a rare dual perspective: he's both building his own company with AI tools and helping create enterprise-grade AI coding infrastructure.Ryan gives us refreshingly honest insights into the hyper-competitive coding agent landscape, why traditional evals don't work for open-ended coding tasks, and the "dirty secret" that most quality decisions still come down to "dev vibes." We dive into the technical reality of competing with well-funded teams, his systematic framework for building with AI agents (which has 5,000+ GitHub stars), and why success isn't just about model capabilities — it's about solving real developer problems through obsessive attention to user experience.Whether you're building AI products or trying to understand what it really takes to compete in this space, Ryan's grounded perspective cuts through the hype with practical lessons from the trenches.Retry

On this episode of Deployed, we talk with Kelly Schaefer, a Product Director at Google Labs and who’s been recognized as one of the Top 100 Women in AI. Kelly has led a portfolio of experimental AI products like NotebookLM and the Jules coding agent. The Google Labs team helps turn DeepMind research into real products that can work at Google scale.She shares what actually works when shipping AI features, from how her teams use evals to drive product quality, to why speed matters more than perfection. We also talk about how PM and UX roles are evolving in the AI era, and why she hires “dot connectors” who can bridge across domains.If you’re building AI products, managing product development teams, or just trying to stay ahead of how this field is evolving, this conversation offers a clear look into what actually works inside one of the world’s most influential AI product orgs.To see more of Kelly and her team’s work, check out https://labs.google/