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Should we revisit Extreme Programming in the age of AI?

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The pace of software output has never been faster. AI tooling and decades of platform innovation have dramatically lowered the barrier to code creation. With just a few prompts or API calls, it is now possible to generate entire products, features, infrastructure, and functionality in hours rather than weeks.

And yet, despite all this acceleration, delivery outcomes remain stubbornly poor. Too many initiatives underdeliver, budgets continue to overrun, and users are left underserved. If cheaper and faster code has not solved delivery, then the bottleneck must lie elsewhere.

Output is not the problem

Typing has never been the bottleneck. We have seen successive waves of acceleration:

The rise of high-level languages

Widespread adoption of frameworks and package managers

The move to DevOps and serverless computing

Developer platforms that abstract away infrastructure

And now, AI-enabled code generation.

Despite this acceleration, outcomes remain stubbornly inconsistent. The long-running Standish Chaos study still finds that most IT projects miss expectations, while McKinsey reports that 70% of digital transformations fail. More output has not meant better software.

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