# Hard Learned Lessons from Over a Decade in AI

Page: https://stenobird.com/podcast/mlops-community/hard-learned-lessons-from-over-a-decade-in-ai
Text version: https://stenobird.com/podcast/mlops-community/hard-learned-lessons-from-over-a-decade-in-ai.md
Podcast: [MLOps.community](https://stenobird.com/podcast/mlops-community)
Published: 2025-06-06T14:53:12+00:00
Episode link: https://podcasters.spotify.com/pod/show/mlops/episodes/Hard-Learned-Lessons-from-Over-a-Decade-in-AI-e33sqrr
Audio file: https://anchor.fm/s/174cb1b8/podcast/play/103754043/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2025-5-6%2F401693141-44100-2-39c89699db12c.mp3
Processing state: processed
JSON: https://stenobird.com/v1/public/podcasts/mlops-community/episodes/hard-learned-lessons-from-over-a-decade-in-ai
Duration seconds: 2922

## Resource

Tecton⁠ Founder and CEO Mike Del Balso talks about what ML/AI use cases are core components generating Millions in revenue. Demetrios and Mike go through the maturity curve that predictive Machine Learning use cases have gone through over the past 5 years, and why a feature store is a primary component of an ML stack. // Bio Mike Del Balso is the CEO and co-founder of Tecton, where he’s building the industry’s first feature platform for real-time ML. Before Tecton, Mike co-created the Uber Michelangelo ML platform. He was also a product manager at Google, where he managed the core ML systems that power Google’s Search Ads business. He studied Applied Science, Electrical & Computer Engineering at the University of Toronto. // Related Links Website: ⁠www.tecton.ai⁠ ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~ Catch all episodes, blogs, newsletters, and more: ⁠https://go.mlops.community/TYExplore⁠ MLOps Swag/Merch: [ ⁠https://shop.mlops.community/⁠ ] Connect with Demetrios on LinkedIn: ⁠/dpbrinkm⁠ Connect with Mike on LinkedIn: ⁠/michaeldelbalso⁠ Timestamps: [00:00] Smarter decisions, less manual work [03:52] Data pipelines: pain and fixes [08:45] Why Tecton was born [11:30] ML use cases shift [14:14] Models for big bets [18:39] Build or buy drama [20:20] Fintech's data playbook [23:52] What really needs real-time [28:07] Speeding up ML delivery [32:09] Valuing ML is tricky [35:29] Simplifying ML toolkits [37:18] AI copilots in action [42:13] AI that fights fraud [45:07] Teaming up across coasts [46:43] Tecton + Generative AI?

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