You can’t predict the future, but you can build the fitness to respond to it. The advantage isn’t prediction. It’s how fast your leadership team can notice and anticipate change and respond. Hence mind candy — an information stream to help you and your team think about what’s next.
60% of custom applications are now built outside of IT
Let that number sink in. The gatekeeping model is already dead. The only question is whether leadership acknowledges it or keeps pretending. This is the citizen development reality. And it’s accelerating. Low-code was visible and containable. AI-generated code is not. It’s diffuse, fast, and much harder to govern.
- https://www.informationweek.com/it-leadership/why-cios-can-t-let-users-wait-on-it
- https://www.forbes.com/councils/forbestechcouncil/2026/03/19/empowering-citizen-developers-without-compromising-security/
The leadership question
Are you ready for autonomy in IT?
The other prompts:
My latests book about books about AI
Data, acceleration, and the future of intelligence: Lessons from 25 core books about AI, technology abstraction, and consciousness. Also available as a board briefing.
https://www.ronimmink.com/product/a-book-about-books-about-ai/
AI Readiness: Why It Starts with Data Quality Basics
Across organizations and government agencies AI has moved from buzzword to board agenda. Leaders are asking, “What’s our AI strategy?” long before they ask, “Is our data ready?”
https://www.comptia.org/en/blog/ai-readiness-why-it-starts-with-data-quality-basics/
Personalisation in the age of ‘zero-party’ trust
Context matters more than cookies
https://www.raconteur.net/technology/personalisation-in-the-age-of-zero-party-trust-2
7 Factors That Drive Returns on AI Investments, According to a New Survey
The seven factors that can drive economic value from AI are: 1) clarity on what kind the organization is trying to achieve, 2) seeking value in both products and processes, 3) using all the tools in the AI toolbox, 4) adopting a framework or method for creating value with AI, 5) involving the finance department in certifying value created with AI, 6) training both users and leaders on AI use, and 7) embracing an economic maturity model to understand how AI is creating value for the organization
https://hbr.org/2026/03/7-factors-that-drive-returns-on-ai-investments-according-to-a-new-survey
Why your observability bill keeps growing (and it’s not your vendor’s fault)
High observability costs? Switching vendors won’t help. Learn to cut bills by fixing data quality at the source.
https://thenewstack.io/why-observability-bills-grow/
“Sensorveillance” turns ordinary life into evidence
The Internet of Things has quietly transformed into a vast surveillance network, turning our most personal devices into digital informants
https://spectrum.ieee.org/digital-surveillance
Why Reinvented Hardware Is the Foundation of Our Intelligent Security Future
Unstructured Data at Scale: Why Legacy Architectures Are Failing
