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.
No time to change: When Knowing There's a Better Way Isn't Enough
Knowing there’s a better way isn’t enough. What stops teams from changing — even when the cost of staying stuck is obvious?
The Comfort of a Bad Outcome
Why do teams cling to broken processes? A UCL study explains more about software delivery than you might expect.
What 'Done' Really Means: The Definition That Changes Everything
A static Definition of Done produces static results. An evolving one creates productive crises that force teams to improve sustainably.
What Happens After Your Two-Year Agile Transformation (And Why Lasting Change Takes Longer Than You Think)
Two years of agile transformation delivers the structure. Lasting change requires building the capability to keep improving. Here’s the difference.
From Scope Arguments to Conversations: What Sprint Planning Should Actually Achieve
When sprint planning focuses on scope instead of value, mid-sprint becomes scope arguments. Here’s what planning should actually achieve.
5 Signs Your Scrum Team Needs External Coaching
When you’re embedded in a system, you can’t see what’s holding you back. Here are five signals worth attending to.
When Velocity Metrics Lie: What Your Sprint Numbers Are Really Telling You
Stable velocity can hide dysfunction. Fluctuating velocity reveals truth. Here’s what your sprint numbers are actually telling you.