Most organizations are running some version of a project operating model or a product operating model - or, more honestly, an uncomfortable mix of both. In this episode, Peter Maddison and Dave Sharrock get into what actually separates these two approaches, where the tensions show up, and why copying what works somewhere else rarely lands the way you expect.

They dig into how the nature of your work - ordered versus unordered, stable versus volatile - should shape how you plan, who holds decision rights, and how closely your experts need to stay involved. They also talk honestly about the hybrid trap: why trying to be all things to all teams usually ends up serving nobody, and what a smarter version of "borrowing from both" can actually look like.

Real examples from large organizations, including a couple of banks, show just how messy it gets when the model is mandated from the top without enough room for context.

Key takeaways from this episode:

• There is no universal operating model. The right fit depends on your context right now, not what worked somewhere else.
• If your plan is constantly changing, lean toward the product side. If it's stable and predictable, the project side probably serves you better.
• Be intentional about your choices. Ask why you're organizing work the way you are, and how you'll know if it's working.
• Getting an outside perspective matters. It's easy to stay stuck in familiar patterns without someone who can see the system clearly and name what isn't working.
• Get your operating model working before you add AI into the mix. Throwing new tools at a system that isn't working yet just breaks things faster.

Which end of the spectrum does your organization sit on right now - and is it actually working for you? Leave a comment below. We read everything.

Product manager. Product owner. Project manager. Three roles that often exist in the same organization, sometimes in the same meeting, and frequently stepping on each other's toes. In this episode, Dave and Peter break down what actually separates these roles, why the confusion happens, and what it costs when the lines blur in the wrong ways.

They dig into the difference between a project-centric operating model and a product operating model, and why that distinction matters more than most organizations realize. They also get into a concept Peter uses with clients: product owners reduce decision latency, project managers reduce reporting latency. It sounds simple, but the implications reach into how teams are funded, how authority is distributed, and why some transformations stall halfway.

The conversation covers real patterns from the field, including what happens when a technical project manager spends most of his time coordinating 14 dependency groups just so a product owner can get a decision made, and what it looks like when a project-centric funding model quietly undermines a product operating model that was never quite finished.

They also touch on where AI fits into all of this, and where it currently falls short as a bridge between these two worlds.

Three key takeaways from this episode:

1. It's not either-or. Both project management and product management are necessary. The goal is to use each skill set in the right place, not to eliminate one in favor of the other.
2. The relationship between product managers and project managers works best as a true peer-to-peer dynamic. Hierarchy between the two tends to break things down quickly.
3. Be clear about decision-making authority. If your product owners don't actually have the autonomy to make decisions, the role isn't working. And if your project managers exist primarily to satisfy a funding model that doesn't match your operating model, that's a signal to look at finishing what you started.

If this is a conversation your team needs to have, share this episode with them. And if you're finding value in Definitely Maybe Agile, follow the show on your favorite podcast platform so you never miss an episode. New conversations drop every week.

Most organizations are somewhere between experimenting with AI agents and quietly hoping nothing breaks in production. Logan Kelly, CEO of Waxle AI, has spent a lot of time in that gap, and he thinks governance is the piece most teams are walking past too quickly.

In this episode, Logan joins Peter and Dave to talk about what agentic governance actually looks like in practice, why a single consistent layer beats a pile of point solutions, and how to keep developers moving fast without letting things go sideways when it counts.

This week's takeaways:

• Let your teams experiment. That's how you learn what agents can actually do. Just don't skip governance on the way to production.
• Governance doesn't have to be a gate. The best version layers in without friction, and gives everyone in the organization visibility, not just the dev team.
• If a developer has to do extra work to implement a governance feature, that's a design problem. Good governance should work for the developer, not the other way around.