Two paths. One stronger practice.

Let's improve your code reviews.

Choose the level of change your organization needs: improve an established review process, or redesign the workflow for AI-assisted development.

01Team workshop

For engineering teamsImprove the existing practice

02Tailored engagement

For engineering leadersRedesign the operating model for AI
01Remove friction from your current process

Practical Team Workshop

Review Performance Workshops

Improve the speed, quality, and effectiveness of your current code review operating model.

Practical, research-based workshops that help teams identify their review bottlenecks, establish better habits, and make feedback more useful.

Choose this path if

  • Reviews are slow or unpredictable
  • Feedback quality varies across the team
  • Review responsibilities and norms are unclear
  • AI increased the review bottleneck

Your team will work on

  • Reducing delays and context switching
  • Giving focused, constructive feedback
  • Building a consistent team review practice
  • Leveraging AI to enhance the review process
See workshop options
02AI is changing how your team creates code

Tailored Engagement for Engineering Leaders

AI Code Review Readiness Sprint

Redesign your review workflow for AI-generated and AI-reviewed code.

A focused engagement to assess your current workflow and design a practical, risk-aware review model that keeps human responsibility clear.

Choose this path if

  • AI is increasing change volume
  • Agents now create or review code
  • Human review effort is not risk-based
  • The current review model needs to be redesigned

The sprint delivers

  • Assessment of current AI and review practices
  • Design of an AI-era code review workflow
  • Human-review guidelines
  • A pilot plan for implementing the new workflow
Discuss a readiness sprint

What each path delivers

Review Performance Workshops

From recurring friction to a stronger, AI-aware review practice.

  1. 01Assessment of current review bottlenecks
  2. 02Shared review principles and responsibilities
  3. 03Better feedback and collaboration practices
  4. 04Work on AI-related friction of current workflow
  5. 05A concrete team improvement plan

AI Code Review Readiness Sprint

From a review model that no longer works to one your team can pilot.

  1. 01Assessment of current AI and code review practices
  2. 02Identification of bottlenecks, risks, and responsibility gaps
  3. 03A future AI-era code review workflow
  4. 04Risk-based human-review guidelines
  5. 05A practical implementation and pilot plan