Issue #66 - Value-driven Prioritisation
How you should choose which data and AI use cases deserve scarce time and money
The Data Ecosystem
Data isn't easy. It's incredibly complex. What is worse though, is nobody appreciates how complex it is. And nobody has really tried to solve it. So enter this newsletter, tackling the must-know parts of the Data Ecosystem one topic at a time!
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Issue #65 – Creating Data & AI Use Cases
Building use cases got faster with AI, but scoping and buy-in are still essential; here's a three-step method and a Spec Kit template for business & tech teams
Issue #64 – Don’t Let Solutions Architecture Disappear
Sure, building products and apps may be easier now with AI, but don’t forget the principles of a good solution!
Issue #63 - The Emergence of AgenticOps
How to create operational discipline for managing your AI agents; no hype included
The OpenAI Model that Could
...Break out of its sandbox, hack a competitor, say sorry, and nothing happens. So, should we be worried?
Issue #62 – Explaining DevOps vs. DataOps
Honestly, there is probably no better time to learn proper DevOps & DataOps principles; here is a quick summary of both and why they matter today
Issue #61 – Evolving the Data & AI Maturity Assessment
Even classic frameworks like Gartner get outdated; this is how you need to start thinking about your data & AI maturity
Fable and Mythos Are Here (well kinda). So What's Next for Human Work?
Hey, even if they are blocked, the tech is here. You need to figure out how to work in this new reality
Consulting in an AI-World is Fine. Big Consulting Isn’t.
AI is putting a dent in a classic business model; and the economics don’t look good
Issue #60 – The Context Moat AI Needs
What a context layer actually is and why it is important in today's AI world