With the dawn of AI development, it’s easy to assume pair programming is becoming less relevant. Why pair with a fallible human when a tireless agent can rapidly generate, validate, and implement ideas?

Interestingly, our appetite for pairing hasn’t gone down, quite the opposite.

So, how is pair programming still relevant in the age of AI?

A) More critical decision-making

AI needs careful instructions to drive maintainable, humanly understandable codebase (which we still think is a critical property to date). The secret sauce is in the context and prompt engineering, where AI is instructed with architectural, design and software principles. As coding is largely offloaded, the non-trivial conversations are now on approach, architecture and design. The assumption of pair programming is that for non-trivial problem-solving, two is better than one.

B) Overcome Review Bottleneck

With accelerated code generation, the amount of code that needs reviewing is vast. PRs have always been a notoriously bad way of reviewing code. At the time of the review, decisions have already been made. Only a few people and teams are shrewd enough to reject PRs altogether, and undo big decisions. Pair Programming means constant peer review, which is a remedy for the accelerated rate of code generation.

C) No Silos

We’ll see that people that are able to effectively use AI, will ship vastly more than counterparts. The high-performers will soon run risk of becoming a silo by the sheer context they hold. Organizationally, it makes sense to not depend on single actors. As a team member it makes sense to share ownership.

Pairing builds resilience through shared understanding, creating a more cohesive and robust engineering organisation.

D) Rapid Learning and growing juniors

Tectonic shifts in methodology and technology mean adaptation and experimentation. Pair programming is an amazing tool for humans to infuse ideas, consolidate thinking and explore with curiosity.

Equally, for less experienced folks, it remains the best tool we know of to learn the craft.

Conclusion

As longtime fans of XP, we’ll admit we felt a momentary existential threat when AI first hit the scene. But pairing was never about two people typing faster—it was about unlocking the right conversations at the right time.

In a world where code is cheap, good decisions are expensive. We’re betting that pairing is the best way to ensure you're making the right ones.