Of loops, layers and links: patterns that cut across domains
3 articles · 18+ years of learnings
My experience spans processes, operations, business, product and technology over 18+ years. I use this space to share learnings from that span: the connections that keep showing up, the ways of thinking that travel with them, and how mental models and tenets reinforce each other in practice.
What to expect: Quality over quantity - fewer pieces, written to earn the read.
Note: I use AI as a virtual, credible “Chief Sparring Officer” for research and heavy lifting on time-consuming tasks. I spend my time on standards, decisions, and iteration so each piece earns the read. The thoughts and ideas are mine.
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AI made product a showing game. Most organisations are still built for telling.
AI collapsed the cost of proving an idea. Prototypes that took weeks now take hours. But the constraint did not disappear. It moved from build cost to evaluation capacity. The organisations that gain from cheap proof are those that build the muscle to evaluate and kill faster, not those that say yes to more.
Read the article · 3 min
AI keeps pushing the automation boundary. Trust decides where each workflow settles.
AI is automating more complex work that spans several systems. Each workflow settles at a different point on the automation spectrum, from AI as a copilot to AI working alone while a person keeps watch. The business sets that point, not the model, and it moves as trust is earned one task at a time. Leaders who design for the decisions AI hands back will get more from it than those chasing full automation everywhere.
Read the article · 5 min
AI is a loudspeaker, not an auto-tuner
AI amplifies the platform it is plugged into and increases the return on foundational work. But it cannot correct what is wrong with that platform. The return on an AI budget is set less by the model you choose than by what your systems of record can expose. Connect an agent to a bad API and you get a faster bad API.
Read the article · 4 min