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Conversations about Kanban, flow metrics, forecasting, and what it actually means to work with Agentic AI.
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Steering by Probability
Building the delivery view leadership actually needed, where every initiative carries the odds it lands rather than a date somebody made up.
Is This How We Want to Spend It?
Six months inside an organization where agents wrote most of the code, and where all that capacity actually went once we looked.
Ungoverned by Default
Why agents quietly drift back to the industry average, and where a rule has to live before it actually holds. The worksheet from the session is on the page.
Why Agile Fails After Consultants Leave
Why Kanban practices quietly stop once the consultant leaves, and what changes when the WIP limits and the board habits live in the agentic framework instead of in somebody’s memory.
Kanban & Agentic AI: Making AI output actually ship
How flow discipline turns raw AI output into finished, predictable delivery, and why the operating model matters as much as the model itself.
AI doesn’t bring waterfall back. It lets you be wrong faster.
AI made building faster, not finding out you were wrong. So a big up-front batch just gets you a bigger, more polished mistake.
AI boosted your throughput. Your strategy didn’t move.
Your throughput went up. Here’s why none of that speed reached the work your leadership cares about, and the one cut of your data that proves it.
AI, Kanban, and a restructure. You can prove something moved, not what moved it.
We delivered four to five times as many work items a month. Here’s why that number holds up, and why I still can’t credit AI for it.
The Kanban Playbook
A practical reference for Kanban practitioners: flow metrics, WIP limits, forecasting, and more. Built to use alongside your coaching and training.
Want to talk flow?
Whether you're dealing with unpredictable delivery, scaling AI output, or just trying to make sense of your metrics, the first conversation is free.