For decades, pair programming has been a much discussed aspect of Extreme Programming (XP): two developers working side by side with the goal of writing better code than either could alone. The benefits are well-documented: a faster path to fewer bugs and higher-quality output. However, the bean counters aren’t a fan - why hire two people for a one person job? 

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But as generative AI starts making its way into the software development process, more developers are starting to partner not with another person, but with artificially intelligent tools. AI-driven coding solutions like Cursor and Cline are seeing enormous popularity amongst developers for their features such as real-time code edits and suggestions, automated debugging, and test generation. 

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While this technology is still evolving, the rapid, widespread adoption across the development community for these tools could signal a change coming to standard workflows as developers get their first taste of XP– and seem to be asking for more.

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Thus far, this change has been largely organic. For technology leaders, embracing and formalizing an AI powered pair programming approach could be a means to navigating dynamic, yet demanding marketplaces, all while saving costs.  

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What Is Pair Programming and Why Has It Been Effective?

Pair programming is a collaborative technique that is core to XP and several other Agile software methodologies. It involves having two developers work together on the same code. While there are multiple styles of pair programming, the most common involves one person (the "driver") writing the code while the other (the "navigator") reviews it in real-time — offering feedback, spotting bugs, and providing guidance.

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This drives the high quality results customers expect, with collaboration and teamwork fostered in a way that is impossible to recreate with solo programming. But the world of software development is evolving and one of the most significant advancements has been the shift from traditional pair programming to AI-assisted programming. 

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Among the many Agile programming methodologies, XP practitioners stand out as being best positioned to leverage AI. That’s because the principles of XP (collaboration, adaptability, and rapid feedback) align perfectly with what AI needs to reach its potential.

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What is Extreme Programming 

Extreme Programming is an Agile software development methodology that centers around collaboration, simplicity, quality, and adaptability. It has historically had poor adoption because it's intense, requires a lot of effort, and feels wasteful to some leaders as they perceive that two people are doing the work of one. 

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However, those who have adopted XP and Agile have found that its core practices of frequent releases, continuous testing, and pair programming make this methodology a good fit for dynamic industries where requirements often change. 

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Why Does Extreme Programming Pair Well with AI? 

The focus on communication and teamwork inherent in this methodology builds a culture where developers are already comfortable working side-by-side. Because the methodology is so intense, these developers have built the muscles required to move quickly without sacrificing quality. So XP practitioners are well positioned to transition from traditional programming into automated AI-assisted workflows. Effectively, the human does much of the “navigating” and the AI does much of the “driving”.

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In addition, XP is purpose built for environments of ambiguity and rapid change — exactly like those that AI has ushered in. Many developers hesitate to adopt new tools or approaches due to steep learning curves or fear of disrupting workflows. But XP practitioners view adaptability as an everyday part of their process and may be more likely to use emerging AI tools, test their impact, and integrate them into daily tasks.

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Generative AI as a Partner in Programming

Generative AI tools are redefining how developers approach their work with advanced features such as code suggestions, debugging, test generation, and documentation. These tools act as intelligent coding assistants, capable of improving productivity in ways that were previously impossible to achieve.  

• Suggest Code in Real Time Generative AI tools can predict what you're trying to accomplish and offer snippets to speed up coding.  In many cases, the AI can write much of the code itself, with humans providing real-time oversight and guidance.
• Debug Issues AI can identify issues, suggest fixes, and even auto-correct errors across multiple files, given error descriptions or log messages.
• Generate Tests Writing tests can be tedious, but AI can help developers identify what to test by analyzing code, generating test cases, and predicting potential problem areas.
• Provide Documentation AI assistants can automatically generate meaningful documentation for the code you write.

For developers, learning how to partner with AI may be the new critical skill for rapid productivity gains while delivering on the quality and adaptability that pair programming is known for.

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Is AI Assisted Pair Programming Right For Your Team?

AI tools have undeniable advantages as the second in a pair programming approach, compared to assigning humans to the task – according to Mckinsey, developers using AI tools performed coding tasks like code generation, refactoring, and documentation 20%-50% faster on average.

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In addition to speed, benefits of AI assisted pair programming include:

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• Error Catching

Errors happen in coding, and they can cause a lot of headache. However, catching these errors isn’t so simple and quality assurance is subject to human oversight. AI can automatically analyze the code and highlight errors with a level of accuracy that would take humans much longer to reach manually. 

• Knowledge Sharing

Getting a developer up and running takes time that the team may not have. However, their input is needed for traditional pair programming to reach its full potential. On the other hand, AI instantly learns from what you feed it, so the driver and navigator (in this case, artificial intelligence) are quickly on the same page. 

• Cost

Pair programming with a human navigator requires paying a second person on every task. Glassdoor estimates that the average salary of just a junior developer is over $94k, so the spend can be cost prohibitive to teams. AI tools can be much cheaper in both the long and short term as they produce faster and work longer than any human team member ever could. 

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However, it’s not all sunshine and roses when it comes to replacing people with technology.

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The Pitfalls of AI in Pair Programming

Not every developer, nor development team is going to be thrilled about the idea of making their new co-worker an LLM. Perhaps where AI most clearly falls short is its ability to solve complex problems, as it is limited to existing data and patterns. Having a human partner encourages innovation through collaboration as each individual provides input into how to overcome challenges. 

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In addition, it takes buy-in from management to adopt pair programming. If leaders have been reluctant to adopt this more expensive approach, then it’s likely that the team will not have the muscle memory to quickly adapt to working in this type of intensive collaborative environment (luckily we know some people you can hire who can help get them up and running!). 

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Ultimately, traditional pair programming excels in complex problem solving and nurturing a team culture. But its benefits can be outweighed by its shortcomings when compared to AI’s speed, accuracy, and cost benefits. 

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The Future of Programming

Pair programming has always been about leveraging collaboration to produce better code—but now, AI is changing the equation. Generative AI tools like Cursor and Cline are proving to be the ideal pair programming partner, offering developers real-time feedback, debugging, and test generation at a scale no human counterpart could match. 

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While AI won’t replace human ingenuity, it removes the friction that has historically made XP and pair programming feel costly or inefficient. For technology leaders, the message is clear: embracing AI-driven pair programming isn’t just about keeping up—it’s about unlocking new levels of speed, quality, and adaptability in software development.

Curious about how to bring AI assisted pair programming to life in your organization? Stride can help, let’s chat. 

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