Successful onboarding of new engineers depends heavily on the environment they enter. Teams with clear code, collaborative culture, and low-risk development practices provide the most supportive space for newcomers. Using Waydev metrics like Knowledge Sharing Index (KSI), review depth, and risk indicators, you can identify teams best suited for onboarding.

Step 1: Look for High Collaboration (High KSI)

➡️ Where: Team Insights → KSI

Teams with a high KSI demonstrate strong knowledge-sharing behaviors, which is crucial for helping new engineers ramp up quickly. It indicates active peer reviews and consistent collaboration across the team.

What to look for:

• Teams where review responsibilities are broadly shared.
• Low dependency on single reviewers (avoid “bus factor” risks).

Step 2: Prioritize Thoroughly Reviewed PRs

➡️ Where: PR Insights → Merge Quality

New engineers thrive in environments where code reviews are rigorous and educational.

What to look for:

• PRs with multiple reviewers and comments.
• Fewer rubber-stamped merges.
• A culture of review that emphasizes learning and shared responsibility.

Step 3: Assess Code Simplicity and Risk

➡️ Where: PR Insights → Risk Metrics / Coding Activity

Instead of focusing solely on low coding time, look for codebases with:

• Low number of high-risk commits
• Minimal legacy refactor work
• Balanced amount of new code vs. rework

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These indicators suggest maintainable, understandable code—ideal for onboarding.

Step 4: Avoid Overloaded or Chaotic Teams

➡️ Where: Team Insights → Workload

Some red flags to watch for:

• High levels of legacy refactor (could imply difficult or outdated codebases).
• Excessive “Help Others” activity (may indicate junior devs creating tech debt that seniors constantly clean up).
• Very low or very high churn (might reflect instability or lack of engagement).
• Balance is key—look for teams with healthy churn, new work, and sustainable review practices.

Key Takeaways

• Use the Workload tab to spot early signs of imbalance in task distribution.
• Monitor task states to ensure work-in-progress limits are respected.
• Uneven ticket counts may require rebalancing to maintain consistent team productivity.