You can’t predict the future. You can build the fitness to respond to it. Mind candy — fuel for strategic conversation about what’s next.
Business risk: The blast radius of not knowing
You can’t predict the future. You can build the fitness to respond to it. #Mindcandy is fuel for strategic conversation about what’s next.
The blast radius of not knowing
Technical debt lives in the code. Cognitive debt lives in the people. It’s the growing gap between how much your AI systems do and how much anyone in the organisation actually understands about what they do. And it’s compounding. AI-generated systems are growing faster than teams can govern them. The understanding doesn’t. Velocity feels real. The debt is invisible. That’s what makes it dangerous — you don’t notice cognitive debt until something breaks and nobody in the room can explain why.
The more you automate without understanding, the faster you erode the judgement that made the automation worth building in the first place. Automate your operations, fine. Automate your moat, and you’ve handed your competitive advantage to a system nobody can interrogate.
- https://siliconangle.com/2026/04/29/cognitive-debt-slow-uptake-strategic-ai-appianworld/
- https://www.oreilly.com/radar/dont-automate-your-moat-matching-ai-autonomy-to-risk-and-competitive-stakes/
Where in your organisation is AI making decisions that no one on your leadership team can explain — and what is that costing you in judgement, governance and strategic control?
The other prompts:
Free downloads
12 free books on strategy, innovation, intrapreneurship, AI, future trends and leadership. Each one distils the best thinking from dozens of business books into a single, actionable read. Every book is also available as a BookBuzz session, board briefing or keynote.
https://www.ronimmink.com/books-by-ron-immink/
Low-code adoption is outrunning governance at most enterprises
Business users get access to a fast, accessible development tool, start building, and skip the fundamentals like training, segmented development environments, data loss prevention policies, formal ownership models. Short-term, things look productive. Longer-term, the organization ends up with an ungoverned sprawl of apps, unclear accountability, and security gaps that are expensive to close.
The Invisible AI Jungle: Enterprises Blind to Rampant Security Risks
Security teams have visibility into only 44% of the AI applications, agents, and automations built by business users. This means the majority of these tools, many of which handle sensitive company and customer data, are operating completely in the shadows, outside the reach of traditional security controls.
https://briefglance.com/articles/the-invisible-ai-jungle-enterprises-blind-to-rampant-security-risks
Beyond the Black Box: the new ‘explainability’ rule for enterprise AI
As the June 2026 deadline for high-risk systems under the EU AI Act nears, businesses must dismantle the ‘black box’ or face exclusion from the European market.
This Founder Watched an AI Agent Destroy 3 Months of Company Data: ‘It Took 9 Seconds
The story of a ‘rogue customer AI’ wreaking havoc is a warning for entrepreneurs eager to harness the power of AI agents.
Divine intervention in AI
Pope Leo warned that AI risks “hollowing out” real human relationships—creating digital environments where people are optimized into bubbles, unable to distinguish truth from simulation
https://www.linkedin.com/pulse/divine-intervention-ai-reid-hoffman-c1zwc/
AI Agents Need More Than Models to Work in the Real World
For AI to work in production, models are not enough. Systems need access to current, external information that can be used directly in decision-making.
https://www.rtinsights.com/ai-agents-need-more-than-models-to-work-in-the-real-world/
