How AI Changes the Way You Pair Program and Run Standups

AI is rapidly reshaping the way software development teams collaborate, transforming core rituals like pair programming and daily standups. While these practices have long been cornerstones of agile development, AI introduces new efficiencies and workflows that can enhance productivity and improve team dynamics. This guide explores the shift from traditional, synchronous collaboration to asynchronous, AI-assisted models. We’ll cover how these new approaches work, their benefits and challenges, and how your team can thoughtfully integrate them.

Traditionally, pair programming involves two developers working together in real-time at one workstation. It’s a synchronous activity focused on producing high-quality code through constant collaboration. AI introduces a new paradigm: asynchronous pair programming with AI agents.

Instead of a human partner, developers collaborate with a sophisticated AI agent. This shifts the interaction from a real-time conversation to a more flexible, turn-based workflow. Here’s how it typically works:

• Task delegation: A developer assigns a coding task to an AI agent, providing clear instructions and context.
• Independent work: The AI agent works on the task autonomously, writing code, running tests, and even debugging issues.
• Review and iteration: The developer reviews the AI’s output, provides feedback, and requests revisions. This cycle continues until the code meets the required standards.

This asynchronous model allows developers to offload time-consuming or repetitive coding tasks, freeing them up to focus on more complex architectural decisions and problem-solving. It’s less about a continuous back-and-forth and more about strategic delegation and review.

The daily standup is a brief, synchronous meeting for teams to align on progress, plans, and blockers. While valuable, it can sometimes feel repetitive or lose focus. AI offers a way to streamline standups and extract more value from them.

AI tools can integrate with project management systems (like Jira or Asana) and communication platforms (like Slack) to automatically gather updates from each team member. Instead of verbally reporting what they did, what they’ll do, and what’s blocking them, team members can have this information compiled for them.

The benefits of AI-generated standup summaries include:

• Time savings: Teams can replace the daily synchronous meeting with a concise, automated summary, freeing up valuable time.
• Better documentation: A written summary provides a clear, searchable record of progress and blockers over time.
• Improved focus: By automating the reporting process, the team can focus discussions on solving critical blockers rather than just relaying information.
• Data analysis: Over time, AI can analyze standup data to identify recurring patterns, highlight potential risks, and provide insights into team velocity.

Integrating AI into pair programming and standups can lead to significant improvements in efficiency, inclusivity, and data-driven decision-making. The table below compares traditional and AI-assisted workflows.

While the benefits are compelling, adopting AI in team rituals isn’t without its challenges.

• Over-reliance on AI: It’s crucial to remember that AI is a tool to augment, not replace, human expertise. Critical thinking and human oversight remain essential.
• Loss of human connection: The spontaneous conversations and relationship-building that happen during traditional pair programming and standups can be lost. Teams need to find new ways to foster connection.
• Tooling and integration: Choosing the right AI tools and integrating them smoothly into your existing workflow requires careful planning and technical effort.
• Setting clear guidelines: Teams need to establish clear rules of engagement for interacting with AI agents to ensure consistency and quality.

To successfully introduce AI into your team’s rituals, consider the following best practices:

• Start small: Begin with a low-risk pilot project. For example, try using an AI agent for a well-defined, non-critical coding task or use an AI tool to summarize standups for a week and see how the team feels.
• Choose the right tools: Evaluate different AI tools based on their capabilities, ease of use, and integration with your existing stack.
• Involve the team: Discuss the goals and potential benefits with your team. Get their input and address any concerns they may have.
• Establish clear guidelines: Create a simple document outlining how and when to use AI tools. For pair programming, this might include standards for writing prompts and reviewing AI-generated code. For standups, it could be a template for what information the AI should capture.
• Iterate and adapt: AI technology and team dynamics are constantly evolving. Regularly review your AI-assisted workflows and be open to making changes based on team feedback.

Safely rolling out and testing new AI-driven workflows is crucial. You don’t want to disrupt your team’s productivity by introducing a tool or process that isn’t ready. This is where feature flags can be incredibly valuable.

With a tool like Kinde, you can use feature flags to introduce AI-assisted processes to a subset of your team. For example, you could enable an AI standup summarization tool for just one squad, gather feedback, and iterate on the process before rolling it out to the entire engineering organization. This allows you to experiment with new ways of working in a controlled and low-risk manner.

• Feature flags