Season 3

AI Meets The Software Delivery Bottleneck
Definitely, Maybe AgileNovember 05, 2026x
238
00:20:0313.81 MB

AI Meets The Software Delivery Bottleneck

AI can push software delivery to machine speed, but your customers, approvals and decisions still move at human speed. That gap decides what AI really changes. Peter Maddison and Dave Sharrock look at the AI software delivery lifecycle through clock speed. Code generation is getting close to machine...

AI in the SDLC Is Only as Good as Its Context
Definitely, Maybe AgileOctober 29, 2026x
237
00:20:4714.3 MB

AI in the SDLC Is Only as Good as Its Context

AI in the software delivery lifecycle is moving faster than any process you can write down. A model that works today may be wrong in a month or two. Dave Sharrock and Peter Maddison unpack what AI is really doing to the SDLC, from ideation and design through build, release, and operations. They star...

Outcomes Over Output with Mik Kersten
Definitely, Maybe AgileOctober 22, 2026x
236
00:35:4724.61 MB

Outcomes Over Output with Mik Kersten

AI can now produce output faster than most organizations can absorb it. Mik Kersten explains why the move from output to outcome has become a leadership job. Mik, author of Project to Product and his new book Output to Outcome, joins Peter and Dave to talk about what happens when coding stops being ...

Is Spec-Driven Development Just Big Upfront Design?
Definitely, Maybe AgileOctober 08, 2026x
235
00:19:3113.44 MB

Is Spec-Driven Development Just Big Upfront Design?

Spec-driven development with AI is getting a lot of attention. Peter and Dave ask when that structure actually helps you, and when it slows you down. They start with the AI SDLC white paper Anthropic recently published. It lays out a structured, spec-driven approach built for consistency. Peter sees...

How to Validate AI Output Before You Trust It
Definitely, Maybe AgileOctober 01, 2026x
234
00:14:4610.18 MB

How to Validate AI Output Before You Trust It

AI agents will tell you everything works. Here is how to validate AI output when the mistakes are ones no human would ever make. Peter and Dave compare notes from building software, training material, and presentations with AI. The problems they keep running into are strange ones: the wrong database...