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.

Most conversations about AI focus on what it can do in a controlled setting. This one doesn't. Callum Sharrock spends his days deploying AI systems in real environments, watching them succeed and fail in ways no simulation predicted, and reporting what he finds. His conclusion? The trend line is steeper than most people realize, and snapshot thinking is getting a lot of organizations into trouble.

Peter Maddison and Dave Sharrock dig into why reliability, not capability, is the real adoption bottleneck right now. They talk through what happens when non-deterministic models get applied to problems that need deterministic answers, why validation and testing are becoming more important than writing the code itself, and how the calculus around decision making is changing fast. If you can build and test something in the time it takes to debate whether to do it, the meeting starts to look like the problem.

They also get into what this means for developers, for leaders, and for anyone trying to figure out where to actually invest their energy right now. The barriers to building have never been lower. That makes the question of what to build more important than ever.

This isn't a conversation about AI hype. It's about what's actually happening at the frontier, and what it means for the way organizations make decisions.

This Week's Takeaways:

1. The barriers to building have never been lower - figuring out what's worth building is now the real work
2. Leadership is shifting toward agency and rapid decision-making, away from top-down strategy setting
3. If you can run the experiment in the time it takes to schedule the meeting about it, run the experiment

If this episode resonated, follow Definitely Maybe Agile wherever you listen to podcasts so you never miss a conversation. And if you know someone spending two hours debating whether to test an idea they could just build, send this one their way. There are plenty more episodes worth your time at definitelymaybeagile.com.

Something is shifting inside organizations right now, and it's creating a split that's hard to ignore. AI is compressing the time it takes to generate, validate, and prototype ideas. Some people inside your org are moving at a completely different speed than the systems built to support them. Peter and Dave are calling it the great decoupling, and it's already happening whether you've noticed it or not.

In this episode, they dig into why acceleration in one part of a system creates pressure everywhere else. When you map the end-to-end journey from idea to live product, you often find 30 to 40 distinct steps. AI is handling a handful of them. The rest? Still waiting on decisions, reviews, and handoffs that haven't changed in years. Development isn't the main blocker anymore. Decision latency is.

They talk through what it looks like when product managers are running parallel experiments and validating ideas in hours, then slamming into unchanged processes for security sign-off, change control, and release management. And why the smartest people on your team are quietly finding workarounds rather than waiting in line, which creates more risk, not less.

This isn't a conversation about AI hype. It's about the real organizational friction that shows up when the pace of work outgrows the systems designed to manage it. And what you can actually do about it.

If your team is moving faster but waiting longer, this one's worth your time.

This Week's Takeaways:

1. Acceleration in one part of the system creates stress everywhere else
2. Map the end-to-end flow before you optimize any single part
3. If it's happening inside your organization, you need to deal with it internally

If this episode resonated, follow Definitely Maybe Agile wherever you listen to podcasts so you never miss a conversation. And if you know someone sitting at one of those 40 steps wondering why everything feels stuck, send this one their way. There are plenty more episodes worth your time at definitelymaybeagile.com.