The CPO Coaching Gap: Leading in the Era of AI-Accelerated Delivery
Why your primary job is no longer reviewing roadmaps, but "debugging" the systems that create them.
I was advising an early-stage fintech recently when one of their product teams walked me through a fully functional, clickable prototype. It wasn't a wireframe. It was working software connected to a test database.
They had built it in an afternoon using an AI coding agent.
The problem? It solved the wrong customer problem entirely.
The team was moving so fast that their standard two-week review cadence couldn't catch them before they built something nobody needed. They had shipped a solution before anyone had aligned on the problem space.
This is the new reality of product leadership.
Marty Cagan has argued for years that coaching is the single most important responsibility of every people manager. He suggests that first-level managers should spend roughly fifty percent of their week coaching their team. The logic is sound: empowered product teams depend not on less leadership, but on better leadership.
But we are running headfirst into a math problem.
AI is enabling teams to ship at a pace that traditional review cycles cannot match. When an engineer and a product manager can spin up a prototype in two hours that used to take four weeks of discussion, your bi-weekly product review becomes a post-mortem instead of a steering mechanism.
If you try to review everything, you become the organization’s biggest bottleneck. If you review nothing, you get chaos, strategic drift, and a fragmented user experience.
The gap between the speed of AI-assisted delivery and the speed of human coaching is widening. I call this the Coaching Gap.
To close it, product leaders must stop reviewing outputs and start debugging the systems that produce them. We need to move from roadmap approval to what I call “Minimally Viable Consistency.”
The Paradox of Pace
The goal of product development is not to ship software faster. The goal is to solve problems faster.
Right now, we are experiencing a paradox. AI acceleration is making some teams feel slower. Why? Because while the cost of writing code has plummeted, the cost of misalignment has skyrocketed.
When a team spends three weeks building a feature, there are dozens of natural check-ins. Daily standups. Design reviews. Architecture syncs. These rituals act as informal coaching moments. They provide natural brakes where a product leader can step in, ask a probing question, and course-correct.
When a team builds that same feature in three days, those natural brakes disappear.
Over the years, I have watched product organizations try to solve this by adding more process. They mandate PRD approvals before any AI tool can be used. They require sign-offs from three different departments. They try to slow the machine down to match their ability to govern it.
This is a losing battle. You cannot govern an exponential technology with a linear approval process.
Instead of slowing the team down, you have to push the governance down into the team itself. You have to encode your coaching into the environment they operate in.
Try This Today
Look at your calendar for the next two weeks. Color-code the meetings where you are acting as a “gate” (approving a decision) versus the meetings where you are acting as a “guide” (setting context or coaching on how to make a decision). If your gate meetings outnumber your guide meetings, your system is already breaking under the speed of AI delivery.
Minimally Viable Consistency
If you cannot review every roadmap item, how do you ensure the product doesn’t turn into a Frankenstein of disconnected features?
You establish Minimally Viable Consistency (MVC).
MVC is the absolute minimum set of constraints required to ensure that autonomous teams build products that feel like they come from the same company, solving problems for the same customer. It is the difference between a guardrail and a gate.
A gate requires a human to open it. A guardrail allows the driver to go as fast as they want, as long as they stay on the road.
To build MVC, you need three components: Strategic Context, Product Principles, and Automated Verification.
1. High-Resolution Strategic Context
Cagan notes that truly empowered teams need the business context that comes from leadership. In the era of AI-accelerated delivery, that context must be high-resolution.
“Increase retention” is low-resolution context. It gives the team a metric, but no boundaries. An AI-assisted team might build a dark-pattern cancellation flow in three days to hit that metric.
“Increase retention by helping users discover the value of our core workflow within their first three sessions, without using restrictive lock-in tactics” is high-resolution context.
When I led product teams at Foodics, Eneco and even at Tamatem (although it wasnt for a long period), the teams that moved the fastest were not the ones with the best engineers. They were the ones who had the clearest understanding of what we were NOT going to do.
High-resolution context acts as a filter. When a team uses an AI agent to generate ten possible solutions to a problem, they use the strategic context to eliminate nine of them before you ever see them.
2.Product Principles as Decision Algorithms
Product principles are often treated as inspirational posters. “Put the customer first.”
“Simplicity matters.” These are useless.
Effective product principles are decision algorithms. They tell a team how to resolve a conflict between two good things.
When a team is moving at AI speed, they will face micro-decisions every hour. Should we optimize for speed of onboarding or completeness of profile data? Should we use a standard UI component or build a custom one for this specific use case?
If they have to ask you, they stop. If they guess wrong, they build technical and UX debt.
A strong product principle looks like this: “We prioritize user control over system automation. When in doubt, ask the user to confirm rather than assuming their intent.”
That is a coaching moment encoded into a sentence. It allows the team to make the decision you would have guided them toward, without you having to be in the room.
3. Shift from Approval to Verification
The hardest shift for a product leader is moving from “I need to approve this before it ships”to “I need to verify this after it ships.”
In an MVC model, you trust the team to use the strategic context and the product principles to make the right calls. You don’t review the PRD. You don’t approve the roadmap.
Instead, you review the outcomes. You look at the telemetry. You watch the session recordings. You review the customer feedback.
If the team shipped something that violates the principles or misses the strategic context, you don’t punish them for shipping it. You use it as a coaching moment to debug the system. Why did the context fail? Were the principles unclear? Did the team lack the necessary skills to evaluate the AI-generated solution?
You are no longer reviewing the roadmap. You are debugging the decision-making engine that created it.
Try This Today
Write down the three most common corrections you make during product reviews. Turn each of those corrections into a “Even Over” principle. For example, if you constantly tell teams to simplify their designs, write: “We value obviousness even over completeness.” Share these three principles with your teams tomorrow.
The New Coaching Cadence
If you are no longer reviewing roadmaps and approving PRDs, what do you do with your time?
You coach. You spend fifty percent of your week developing the skills of your people. But the cadence of that coaching must change. You cannot coach a team moving at AI speed with a monthly 1-on-1.
The new coaching cadence is continuous, asynchronous, and focused on judgment.
1. Continuous Context Setting
The most valuable coaching you can provide is setting the context for the team. This is not a one-time event at the beginning of a quarter. It is a continuous process of refining the team’s understanding of the market, the customer, and the strategy.
When a competitor launches a new feature, you don’t tell the team to copy it. You use it as a coaching moment to explain why it matters or why it doesn’t.
When a customer churns, you don’t tell the team to build a win-back feature. You use it as a coaching moment to explore the root cause of the churn.
You are constantly feeding the team high-resolution context so they can make better decisions when they are moving fast.
2. Asynchronous Verification
If you are verifying outcomes instead of approving roadmaps, you can do this asynchronously.
You don’t need a two-hour meeting to review a prototype. You can watch a five-minute video walkthrough recorded by the product manager.
You don’t need a weekly status update to know if a feature is working. You can look at the dashboard.
This frees up your calendar to focus on the highest-leverage coaching moments: the times when the team is stuck, when they are facing a novel problem, or when they need help resolving a conflict between principles.
3. Coaching for Judgment
The most important skill a product manager needs in the era of AI-accelerated delivery is judgment.
AI can write the code. It can generate the copy. It can analyze the data.
It cannot decide what matters. It cannot evaluate the trade-offs between two competing priorities. It cannot build conviction in a team.
Your coaching must shift from teaching execution skills (how to write a PRD, how to run a sprint) to teaching judgment skills (how to evaluate an AI-generated solution, how to balance speed and quality, how to resolve conflicts between principles).
When a product manager brings you a problem, you don’t give them the answer. You ask them how they would use the strategic context and the product principles to solve it.
You are not teaching them how to do the work. You are teaching them how to think about the work.
Try This Today
In your next 1 -on- 1 with a product manager, don’t ask for a status update. Ask them to walk you through the hardest decision they had to make this week. Ask them how they evaluated the trade-offs. Ask them what principles they used to guide their decision. If they struggle to answer, you have found your next coaching opportunity.
The Final Check
The transition from roadmap reviewer to system debugger is uncomfortable. It requires you to give up control in exchange for speed and scale.
It requires you to trust that the strategic context and the product principles you have established are strong enough to guide the team when you are not in the room.
It requires you to accept that teams will make mistakes, and that those mistakes are the price of learning and moving fast.
But the alternative is worse.
If you try to hold onto the old model of product leadership, you will become the bottleneck.
Your teams will slow down. Your competitors will move faster. And the AI tools that were supposed to accelerate your delivery will instead accelerate your obsolescence.
The product leaders who thrive in this new era will be the ones who realize that their primary job is not to build the product. Their primary job is to build the team that builds the product.
And you cannot do that if you are spending all your time reviewing roadmaps.