How to Fairly Assign Pair Programming Partners and Code Reviewers on Engineering Teams

Does your team always end up pairing with the same people for pair programming or code reviews?

In engineering teams, pair programming and code reviews are cornerstones of knowledge sharing and code quality. But when pairings become fixed, knowledge silos grow and the team's overall growth stalls. This article covers fair and effective methods for pairing and review assignment, along with best practices that promote knowledge sharing.

Three Reasons Pairings Become Fixed

People Gravitate Toward "Easy" Partners

Experienced engineers naturally tend to pair with each other, or with people they get along with. Some actively avoid specific team members they find difficult to work with. The result is uneven knowledge distribution, new hires feeling isolated, and a declining bus factor (the risk of everything falling apart when a key person leaves).

As fixed pairings deepen, only a handful of people understand certain modules or services. When one of them goes on vacation or transfers, the entire team struggles. Knowledge silos are a serious risk to product stability.

Code Reviews Run on an "Asking" Basis

When someone opens a PR and posts "Can someone review this?", the quickest responder ends up reviewing every time. The workload concentrates on senior engineers, while junior engineers never get the chance to review. This pattern leads to both bottlenecks and burnout.

On top of that, reviewing skills don't develop across the team. Code review is training in reading code you didn't write, and an opportunity to deepen your understanding of design and architecture. When only certain members handle reviews, this learning opportunity doesn't reach the whole team.

The "Invisible Wall" of Remote Work

In an office, you can casually start pair programming with the person sitting next to you. Working remotely, many people find it hard to "reach out," so they end up pairing with the same people. New combinations don't form, and silos within the team deepen.

In remote settings, communication tends to default to text chat. Activities like pair programming that require close collaboration happen less frequently unless you deliberately build systems for them. Having the right tools (VS Code Live Share, Tuple, etc.) and scheduling pairing sessions are key to making remote pair programming work.

Five Principles for Fair Pairing and Review Assignment

Rotation

Change pairs weekly so everyone works together within a month. This broadens knowledge and creates exposure to diverse perspectives. Adjust the rotation frequency based on team size -- weekly for teams of five or fewer, biweekly for teams of ten or more is practical.

Skill Balance

Be intentional about pairing people with different expertise -- senior with junior, frontend with backend. This drives knowledge transfer and develops T-shaped skills (broad knowledge combined with one deep specialty).

Creating a skill matrix helps make pairing decisions smoother. List each team member's strengths and areas they want to develop, and reference it when forming pairs. For example, pairing someone well-versed in infrastructure with someone who wants to learn infrastructure creates natural knowledge transfer.

Random Elements

Purely rule-based pairings become predictable. Introducing randomness in about 30% of assignments keeps things fresh and sparks unexpected discoveries. Having a random slot creates a sense of anticipation -- "Who will I pair with this week?" -- which helps maintain enthusiasm for pair programming.

Transparency

Document the rules for pairing and review assignment so anyone can check them. Being able to explain "Why this pairing?" builds team buy-in. Recording the rules in a team wiki or README also makes onboarding new members smoother.

Load Balancing

Make code review counts visible and set monthly targets to prevent work from concentrating on specific people. This directly addresses bottlenecks and prevents burnout. Using GitHub Insights or a spreadsheet to review each member's review count on a weekly basis is effective.

Practical Workflow

Monday Pairing Decision (10 Minutes)

Start by reviewing the team's skill matrix. Understand the ratio of senior, mid-level, and junior engineers, then determine rule-based pairings (about 70% of the total). The default is senior-junior pairings, with senior-senior pairings assigned to high-difficulty tasks.

The remaining 30% is determined randomly. Create an event on Amida-san, have all engineers add their rungs, then reveal the results. The random slot creates a sense of "Who will I pair with this week?" which prevents monotony.

Post the final pairings to Slack or Notion and share them with the entire team. If schedule changes are needed later in the week, announce them in the channel to maintain transparency.

Code Review Assignment

Automate PR assignments to prioritize team members with the fewest reviews (using GitHub Actions, for example). If automation isn't feasible, track review counts in a spreadsheet and use it as a reference for assignment.

Additionally, hold a weekly "random review" where a few PRs from the week are selected and reviewed by someone who wouldn't normally handle them. Reading unfamiliar parts of the codebase improves the entire team's code comprehension.

Set a minimum reviewer count as well. Requiring at least two approvals reduces the risk of a single reviewer missing something.

Tips for Successful Remote Pair Programming

For remote pair programming, tool selection and session structure matter. VS Code Live Share is free to use and enables real-time code sharing and terminal sharing. Tuple is purpose-built for pair programming, offering high-quality screen sharing and smooth driver-navigator switching.

Sessions should run 25 to 50 minutes. Too long and focus drops; too short and you barely get started. Cycling through 25 minutes of pair programming plus 5 minutes of break, like the Pomodoro Technique, works well.

Establishing a rule to switch driver (the person writing code) and navigator (the person directing) roles every 15 minutes keeps both parties actively engaged and maximizes learning.

Expected Benefits from Adoption

The variety of pair combinations increases, and review workload imbalances are resolved. Junior engineers ramp up faster, and the bus factor improves. In the short term, productivity may dip while people adjust to new partners, but after about a month, the effects of knowledge sharing kick in and overall team productivity starts improving.

As pairing combinations increase, communication volume across the team naturally rises. When team members who don't normally interact work together, mutual understanding deepens and psychological safety improves.

Common Barriers and How to Address Them

"It'll Slow Us Down"

Pair programming assigns two engineers to a single task, which can look inefficient at first glance. However, design mistakes and implementation errors are caught early, dramatically reducing the cost of bug fixes downstream. Code quality also improves, and review cycles shorten.

When proposing it to your team, start with a trial run for one sprint and measure changes in bug rates and review turnaround times. Data-driven decisions make it much easier to win over team members.

Accommodating Members Who Dislike Pair Programming

Not everyone enjoys pair programming. Some prefer focused solo work, and others feel uncomfortable writing code in front of someone.

Don't force it -- offer options instead. Alternating between "pair programming weeks" and "solo work weeks," or stating clearly that pair programming is recommended but not mandatory, are effective approaches. Starting with fewer pairing sessions and gradually increasing them as people get comfortable also works well.

Running It on Small Teams

On teams of five or fewer, rotation combinations cycle through quickly. In this case, you can reduce pairing frequency or set up joint pairing sessions with adjacent teams. Cross-team pair programming contributes to knowledge sharing across the organization.

Frequently Asked Questions

Can it integrate with GitHub/GitLab?

Currently it's manual integration. Determine pairs on Amida-san, post the results to Slack or Notion, and set GitHub/GitLab assignments manually.

What if someone doesn't like pair programming?

Don't force it -- offer options. Alternating between "pair programming weeks" and "solo work weeks," or making it clear that pair programming is recommended but not required, are effective approaches.

Won't code review quality suffer?

Create a review checklist and require a minimum of two approvals to maintain quality. When less experienced members join the review, combine their review with a final check by a senior engineer.

What remote pair programming tools do you recommend?

The three main options are VS Code Live Share, Tuple, and Zoom screen sharing. VS Code Live Share is free and easy to adopt. Tuple is purpose-built for pair programming and offers strong usability. Choose based on your team's budget and workflow.

Summary

Knowledge sharing and preventing knowledge silos in engineering teams starts with a fair, transparent pairing system. Rotate so everyone pairs with each other, consider skill balance, and keep things fresh with random elements. These three points alone can significantly change the pace of team growth.

Start by visualizing the past month's pair combinations and code review counts. Once you can see where the imbalances are, the path to improvement becomes clear.

Related articles:

• Team Building Best Practices
• Improving Remote Team Engagement
• How to Achieve Fair Role Assignment