The ‘No More Individual Contributors’ Framework: AI Team Management in Enterprise
In episode eight of DatAInnovators & Builders Podcast, Michael Domanic, VP at UserTesting, explains how enterprises run AI teams of three to drive transformation.
Hosted by Saket Saurabh, CEO of Nexla, each episode features conversations with CDOs, CTOs, and data architects who’ve built systems at scale. No vendor pitches. No theoretical frameworks that fall apart in production. Just honest discussions about what works when you’re dealing with data variety, stuck AI pilots, or architectures that somehow got more complex in the cloud.
Most data content today falls into two camps: polished conference panels that skip the hard parts, or vendor-funded thought leadership that’s really just a sales pitch in disguise.
This podcast exists in the white space between them.
Every episode breaks down real architecture decisions, team structures, and hard-won lessons from leaders who’ve actually shipped. For example, why most AI adoption stalls at the process level, how to handle data variety across 1000+ business systems, or when to use fine-tuning vs RAG for production agents — the stuff that doesn’t make it into the case studies.
You’ll hear about:
New episodes drop every two weeks on Apple Podcasts, Spotify, and YouTube.
Episode 1 features Robin Sutara, Field Chief Data Strategy Officer at Databricks, on why AI adoption stalls and how to fix it at the process level.
Coming up this season:
Subscribe wherever you listen to podcasts, or watch full episodes on our YouTube channel.
If you’re a data leader with a story worth sharing, reach out. We’re always looking for guests looking to share their lessons learned.
In episode eight of DatAInnovators & Builders Podcast, Michael Domanic, VP at UserTesting, explains how enterprises run AI teams of three to drive transformation.
In episode seven of DatAInnovators & Builders Podcast, Rowan Trollope, CEO of Redis, explains how teams hit 95% cache and cut LLM costs 70% using agent memory, semantic layers, and production-grade AI infrastructure.
Nexla and Vespa.ai partner to simplify real-time enterprise AI search, connecting 500+ data sources to power RAG, vector retrieval, and AI apps.