The Cost-of-Change Curve Is Wrong (Here’s Why)

Описание: The cost-of-change curve has shaped how software teams manage projects for decades. It suggests that the later a change happens in development, the more expensive it becomes. But in modern software development — especially with agile practices, automated testing, continuous integration, and AI-assisted development — that assumption no longer holds the way it once did.

In this video, we explore why the traditional cost-of-change model from the 1970s and 1980s is increasingly outdated. Advances in tooling, agile practices, and now AI have dramatically reduced the cost and risk of modifying software later in the development process.

But while the cost of writing and revising code has dropped, a new constraint has emerged: feedback delay. The real bottleneck in modern product development is no longer implementation — it's learning what to build and getting fast feedback from users.

This shift has important implications for how leaders manage product teams. Many organizations still rely on approval processes and planning assumptions designed for a world where late changes were catastrophic. In reality, adaptability and fast learning now matter far more than perfect upfront requirements.

If you're working with Agile, Scrum, product development, or AI-powered software teams, understanding this shift is critical.

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Chapters
00:00 The Cost-of-Change Curve Explained
00:19 Why Late Changes Used to Be Expensive
01:04 How Agile Reduced the Cost of Change
01:23 Why AI Accelerates the Shift
02:06 The Real Cost of Change Today
02:36 What This Means for Managers
03:22 Adaptability Beats Accuracy