Earlier this year I wrote about how AI can enhance Agile coaching by supporting, not replacing, human coaches. That piece focused on how technology can help coaches increase their impact by amplifying clarity, feedback loops, and decision-making.
But lately, I’ve been noticing a different kind of shift.
AI tools like GitHub Copilot, Augment, and Tabnine are changing the way we develop software. Developers who once spent only a quarter of their time actually writing code are now spending closer to 50 or 60 percent of their time in the IDE. That shift sounds like a productivity win, and it is. But there’s a blind spot forming in the background.
The rest of the delivery system hasn’t caught up.
Product planning, cross-team coordination, architecture alignment, prioritization, user story breakdown. These still happen at human speed. The result? We’re producing more code, faster than ever, but with the same organizational drag. And that creates a new problem:
Coordination debt.
It’s growing faster than technical debt, and it’s quietly threatening to undo the speed gains AI is bringing to software delivery.
The Coordination Bottleneck
Agile has always been about improving flow: faster feedback loops, tighter collaboration, smaller batches. And for a while, that was enough. But now AI is handling much of the rote coding work. Teams are moving faster by default, and the traditional Agile gains aren’t the differentiator they used to be.
Here’s the problem. All of the systems around the work haven’t evolved. Coordination still depends on human cadence. Product teams are still using outdated planning models. Communication is still locked inside meetings. And AI tools, while powerful, can’t resolve ambiguity or surface misalignment on their own.
The myth of the AI developer as a plug-and-play team member is already falling apart. AI doesn’t challenge bad stories. It doesn’t identify risks upstream. It doesn’t facilitate cross-team clarity. So while throughput increases, the ability to keep work coherent hasn’t. That’s where coordination debt begins to stack up.
Coaching in the Age of AI
This is where Agile coaching comes back into focus. Not to reintroduce legacy frameworks, but to guide teams and organizations through the next evolution of delivery.
So what does it look like to coach in this environment?
We help teams redistribute work intelligently. When AI takes on low-complexity coding, coaches help teams rebalance where human energy should go: better refinement, tighter alignment, stronger system thinking. Not everything needs to be faster. Some things need to be clearer.
We introduce collaboration patterns that scale. Async rituals, lightweight checkpoints, documented assumptions. We teach teams how to collaborate when not every contributor is a person, and when the pace of change exceeds meeting schedules.
We support product clarity and prioritization. AI expands the backlog exponentially. Coaching helps teams separate noise from signal and bring product thinking back to the forefront. It’s not about doing more. It’s about delivering what matters.
We coach leadership on realism. More code doesn’t mean more value. Coaching shifts the conversation from volume to flow, from busyness to purpose. That’s not a soft skill. That’s a survival skill.
This Is Agile 4.0
We’re past the team-level basics. We’re past the scaling debates. We’re past portfolio alignment.
Now we’re dealing with a new generation of problems:
- Machine-assisted iteration
- Human-AI pairing dynamics
- Coordinating delivery at a tempo machines have redefined
Agile is evolving again. The frameworks will shift. The practices will adapt. But the core remains the same:
Individuals and interactions over processes and tools.
Even when one of those individuals is no longer human.
