MLOps Community Podcast

Guthrie Cooper (Senior Group Product Manager, AI & Robotics) and Nidhi Sharma (Global Head of Engineering AI & Incubation) from Just Eat Takeaway.com join the MLOps.community to pull back the curtain on how one of Europe's largest food delivery platforms is running an internal innovation engine. From autonomous delivery robots to agentic AI voice assistants, they share what it actually takes to build like a startup inside a 40,000-person company.

Pramod Krishnan is a Managing Director - AI Managed Services at PwC, specializing in enterprise AI transformation — helping large organizations move from AI experimentation to production operating models. In this episode with Demetrios, Pramod breaks down exactly what the OpenClaw wave means for enterprises, and the control frameworks PwC uses before a single agent touches production.

Rafael (Head of Innovation, iFood) and Daniel (Data and AI Manager, iFood) pull back the curtain on ILO-Agent — iFood's conversational AI ordering system built for 200 million users across Latin America. Recorded live at AI House Amsterdam, this conversation goes deep on the engineering and product decisions behind building recommendation systems, agentic AI, and why the speed of your AI's response might actually be destroying user trust.

Before MCP was a standard and before LangChain was widely adopted, his team had already shipped their own orchestration layer and tool protocol in production. This conversation is a rare look at what it takes to build an agentic system that actually books trips, runs on WhatsApp, and keeps adding capabilities without falling over.

Jesse Vincent breaks down how modern “agentic” software development is shifting from writing code to managing intelligent systems. He shares how his Superpowers toolkit uses structured workflows, skills, and subagents to turn vague ideas into executable plans—emphasizing that clarity of intent matters more than coding itself. The conversation explores how AI agents can be guided using psychology, why separating roles (planner, implementer, reviewer) leads to better outcomes, and how iteration—not perfection—builds powerful workflows. Ultimately, the future of software isn’t code—it’s specs, judgment, and orchestrating agents to do the work.

Most teams treat evals like a last-minute checkbox—ship first, panic later—but that’s exactly backwards. The real edge comes from treating evals as a continuous, evolving system from day one, not a static test suite. Because here’s the uncomfortable truth: LLMs don’t fail cleanly or consistently, and neither do your users. If you’re not constantly adapting how you evaluate, you’re basically flying blind—just with more features to hide it.

Conversation with Mihail Eric on how agent-driven development is reshaping engineering work, faster iteration, new failure modes, and shifting team dynamics. Focus on validation, cost tradeoffs, and what breaks when code is mostly generated rather than written.