Agreeing on an idea doesn't mean you both understood the same thing. Dave Sharrock and Peter Maddison dig into why shared context breaks down in practice, and how AI makes that problem harder to ignore.

This week's takeaways:

• Intent is always imperfect. Define how you'll validate it, not just what it is.
• Ambiguity in context isn't a bug. It's necessary. Validation is how you confirm you're aligned.
• Drive down the cost of validation, not just the cost of building.

If this landed, share it with someone navigating the same tension. And reach out at feedback@definitelymaybeagile.com - we read everything.

It doesn't happen all at once. A great idea comes out of a strategy session. Someone turns it into a PowerPoint. Another person summarizes that PowerPoint with AI. By the time it reaches the team building it, the sharp edges are gone and nobody quite remembers what made the idea worth pursuing in the first place.

Peter and Dave dig into a problem that's older than AI but getting harder to ignore. How does intent get lost as it travels through layers of people, tools, and artifacts? What does a shared context document do that a business case can't? And what can the architectural world teach the product world about keeping the thread from unraveling?

Key takeaways:

• Moving artifacts backwards and forwards through an organization strips out nuance at every step. A single central context document is a more honest way to carry intent from strategy to delivery.
• AI is being actively encouraged in most organizations right now, and in using it, teams may be quietly eroding the ideas behind what they're building without realizing it.
• If your outcomes don't match your original intent, the handoff chain is usually where things went wrong. That's worth looking at before blaming the team.

Try this: Trace one idea from your last strategy session all the way to what actually got built. See if you can find where it changed. Then come tell us what you found at feedback@definitelymaybeagile.com.

Most organizations think they have a capacity problem. They usually don't.

What they have is a work-in-progress problem. And those two things call for very different solutions.

In this episode, Peter Maddison and Dave Sharrock dig into one of the most persistent headaches in organizational management: capacity tracking. Why does the instinct to measure utilization backfire? Why does loading people up to 100% actually slow things down? And what should leaders be asking instead?

The conversation covers the real cost of context switching, why that "nearly done" project is probably further away than it looks, and how AI is making all of this more urgent, not easier.

Three things to take away from this episode:

1. 100% utilization is not a goal. It's a warning sign.
2. The right question isn't "how much capacity do we have?" It's "how much work in progress can we actually sustain?
3. AI accelerates your breaking points.

If this conversation resonated, there's more where it came from. Peter Maddison and Dave Sharrock explore these kinds of organizational challenges every week on Definitely Maybe Agile - the podcast that gets into the real complexity of modern ways of working, without the buzzwords.

Listen wherever you get your podcasts, or visit definitelymaybeagile.com to catch up on past episodes and reach out with your own questions.