[kevinstumpf]

(Tecton CTO here) You’re absolutely right that ML projects can’t be solved with technology alone. Besides the right tooling, they also require process, organizational setup, buy-in from multiple stakeholders, etc. By itself, no technology will turn a company into an “ML-first” company. Both technology and organizational problems need to be solved.

A while back, we published a blog post that discusses how we approached these organizational challenges at Uber: https://eng.uber.com/scaling-michelangelo/. With Michelangelo, we found that the right tooling can both solve technical challenges and help with some organizational challenges. For example: If a standardized and centralized platform is the path of least resistance to get ML into production and solve your business problem, you get the organizational benefits of that centralization (governance/visibility/collaboration) along the way.