You Think You Have a Velocity Problem. You Have an Undefined 'Done' Problem
Your velocity chart looks broken. Is the team actually slower — or did “done” quietly stop meaning the same thing to everyone?
The Improvement That Went Nowhere
She mapped the problem, built the solution, engaged the team. Then nothing moved. Here’s what nobody told her about her organisation.
Green Builds Don't Mean You Built the Right Thing
A green build tells you the code works. It doesn’t tell you it solves the right problem. Here’s the gap AI widens.
The Lever Most CTOs Reach for First Isn't the One Attached to Delivery
You tightened AI adoption. Delivery didn’t move. Maybe the lever you pulled was never connected to your organisation’s real constraint.
The Missing 'So That': A Case Study in Distance
AI can write a user story. It can’t have the conversation that makes it mean something. A case study in distance.
Faster Delivery Doesn't Fix an Unclear Backlog
AI makes your team faster. It won’t tell you what’s worth building. Here’s why the backlog question still comes first
Two conversations, one question: what matters more than speed
Two client conversations, one lesson: no AI model or management conviction replaces listening before deciding how fast to move.
10x Productivity: What the Promise Leaves Unaccounted For
Your team’s “10x” AI-accelerated capacity isn’t stable — it fluctuates unpredictably. Is your planning accounting for that?
The Bottleneck Was Never in the Coding
AI coding assistants promise faster delivery. But what if coding was never the bottleneck? A queueing theory perspective.
The Variation You Know vs. The Variation You Don't
Are AI coding assistants reducing variation in your team — or just making it invisible? The evidence cycle is younger than you think.