ThinkData Podcast

What happens when AI can browse, understand, and interact with the web just like a human?
This week on the ThinkData Podcast, I'm joined by Abhishek Das, Co-founder and Co-CEO of Yutori.
Before founding Yutori, Abhishek was a research scientist at Meta, where he worked on AI agents long before the recent explosion in generative AI.
Today, Yutori is building specialised AI models designed specifically for web agents—systems capable of navigating websites, completing tasks and operating autonomously in complex online environments.
In this episode we discuss:
• Why specialised AI models outperform general-purpose LLMs for web automation
• The biggest technical challenges of building reliable AI agents
• Why AI demonstrations often fail in production
• Product-market fit in one of AI's fastest-moving markets
• What founders consistently underestimate when building AI companies
• How AI agents could fundamentally change the way businesses and consumers use the internet
If you're interested in AI infrastructure, startups, product, engineering, or the future of autonomous software, this is an episode you won't want to miss.

Enterprise data has never been more valuable, yet most companies still struggle to answer simple business questions.
This week, I sat down with Ethan Ding, Co-Founder and CEO of TextQL, to discuss why traditional analytics tools weren't built for the age of AI, how autonomous agents are changing enterprise infrastructure, and what happens when AI starts generating thousands of queries where humans once generated dozens.
We discuss:
• Why today's BI tools are reaching their limits
• The biggest technical challenges behind enterprise AI
• How TextQL is rethinking the modern data warehouse
• Why data analysts aren't disappearing—but their jobs are changing
• Finding product-market fit in one of AI's most competitive markets
• What enterprise software looks like over the next five years
If you're building, investing in, or buying AI products, this is a conversation you won't want to miss.

Agentic engineering is quickly becoming one of the most important shifts in software development.
In this episode, I sit down with Scott Breitenother, Co-Founder & CEO of Kilo Code, to discuss why individual coding assistants won't drive the future of software development, but by autonomous AI agents capable of planning, building, testing, and shipping software.
Scott shares the journey from building and selling Brooklyn Data Company to launching Kilo, an open-source agentic engineering platform designed to help developers become dramatically more productive in the AI era.
We discussed product-market fit, engineering adoption, the realities of competing with Cursor, Copilot, and Claude Code, and what engineering leaders should be thinking about as AI fundamentally changes how software teams operate.
If you're a founder, engineering leader, developer, or simply interested in the future of AI-powered software development, this is an episode you won't want to miss.

In this episode of the ThinkData Podcast, I welcome back Dimer Health Co-Founders Carrie Hodge, Sarig Reichert, alongside Chief Medical Officer Dr. David Feldman.
Fresh off the announcement of their $13.5 million Series A, the team discusses why the 30 days following hospital discharge remain one of the most broken parts of healthcare, and how Dimer is using clinician-led AI to transform patient outcomes.
The conversation covers scaling after fundraising, building culture during hypergrowth, the realities of operating at Series A, and what it takes to create a new layer of healthcare infrastructure.

Today, we’re getting into where AI actually fits in the finance stack and why most teams are getting it wrong.
I’m joined by Deepak Bapat, CTO and co-founder of Tabs, an AI-native platform automating contract-to-cash end-to-end.
We cover:
The difference between AI-native vs AI-layered products
Why finance has near-zero tolerance for AI errors
The technical challenge of automating contract-to-cash workflows
Integrating AI into fragmented ERP ecosystems
What finance teams may look like in the next 3–5 years as AI agents take over operational workflows

A really interesting conversation around where AI creates real operational leverage, and where the hype still outweighs the reality.