Enterprise AI needs data, the 3 B's, have you tried using a to do list?

“1978 Chrysler New Yorker.”Monolithic Transformation revisitedRyan re-read my 2019 book on improving your application strategy, mostly at large organizations: The message is as relevant now as it was in 2019: success comes down to nailing the basics - ship fast, iterate faster, and keep the user front and center. Coté’s framework of small-batch thinking, cross-functional teams, and user-first design isn’t theory - it’s a map for organizations to fundamentally rethink how they deliver software.

Our Favorite Management Tips of 2024 - “Add up your total score. If you rated any of these items a 4 or a 5, you have some workaholic tendencies. But if your total score is 15 or above, you’re displaying significant signs of workaholism."

How Do You Create AI Advantage? - You’re going to need access to all that data you have. Historically, this is a very difficult problem in large enterprises and is rarely solved well. For example, are you satisfied with your CRM? For all your enterprise AI hopes and dreams, focus on that first. // “Develop your firm’s knowledge capacity by inventorying your knowledge assets; make sure that you have a plan to build proprietary advantage with the knowledge you’ve captured, and begin the process of capturing tacit knowledge to sustain that advantage.” // Related data wrangling commentary.

PaaS is Better Than Kubernetes

CaaS ProblemsNicky lists the advantages of a real platform over Kubernetes. The platform is Cloud Foundry, and it’s been in development and use for many years, all ready to use. Building platformsI think he goes a little strong on the “sometimes Kubernetes is good for…” part, but that’s mandatory seasoning for such commentary.I don’t hear a lot of people saying “we love Kubernetes!” This is especially true at “normal” organizations. Those that don’t complain (too much) have built layer upon layer of platform-code on-top of Kubernetes and tooling around it, hiding it from developers and even operators.