AI-Changed Bottlenecks: A Scrum Team's Comprehensive Guide to Adjusting WIP Limits

Artificial intelligence tools are fundamentally reshaping our software development processes. Where coding a task once took days, AI-powered tools can now generate draft code in minutes. This acceleration is undeniably exciting, but it also shifts the bottlenecks in our workflow to entirely new points.

With the integration of AI tools into the workflow, the bottlenecks in software development teams' processes have shifted. AI accelerates code production, often creating new or more pronounced bottlenecks in subsequent stages such as code review, detailed testing, integration, and deployment. For instance, the 'Voyager' Scrum team, after seeing a 50% increase in code generation from AI, suddenly found their code review queues growing unmanageably long and their testing processes unable to keep up. They went from saying, 'We can't write code fast enough' to 'We can't review the code we've written fast enough.'

To adapt to these new dynamics, Scrum teams must carefully adjust their Work-In-Progress (WIP) limits to optimize flow and accelerate value delivery. This guide offers a practical framework to manage these AI-changed bottlenecks and enhance your team's efficiency.

Work-In-Progress (WIP) limits restrict the number of tasks being worked on at any given time, thereby increasing focus, reducing context-switching costs, and accelerating flow. With the speed brought by AI, WIP limits cease to be merely a restriction tool; they become a critical balancing element that prevents team overload and maintains quality.

While AI offers the potential for generating more code, using this potential unchecked can lead to the team drowning in subsequent steps. High WIP means teams try to do too many things at once and finish none of them on time. This leads to demotivation, increased errors, and customer dissatisfaction. Properly adjusted WIP limits ensure the team works at a sustainable pace and that the value produced is genuinely delivered.

Adjusting WIP limits is not a one-time fix but a continuous process of experimentation and learning. Here's a step-by-step framework Scrum teams can use to adjust their WIP limits in this new AI era:

The Voyager team, a 6-person software development group, eagerly embraced AI-assisted code generation, initially experiencing a surge of excitement. However, they soon found themselves overwhelmed as the sheer volume of AI-generated code choked their code review and manual testing processes. Team members began losing motivation as unfinished work piled up. The Scrum Master noticed the pattern and brought it up in a retrospective.

The team mapped their value stream and identified code review and testing as their biggest bottlenecks. Experimentally, they reduced the WIP limit for code review to 3 and for testing to 2. While they initially faced some resistance, they soon began to see positive effects. Code review times shortened, testing processes became more manageable, and most importantly, team members could focus better on their tasks with less context switching. This marked the moment the Voyager team truly began to harness the power of AI, but by managing it intelligently.

There are several common mistakes teams make when adjusting WIP limits. The first is treating limits as static and unchangeable. In a constantly evolving environment like AI, limits must be dynamic and reviewed regularly. A second mistake is ignoring the human factor. WIP limits are not just numbers; they also affect team well-being, focus, and collaboration. Team members' feedback is vital in adjusting limits.

Thirdly, focusing on one stage while neglecting others is also a pitfall. AI's impact extends across the entire value stream, so the whole process needs to be considered holistically. Finally, changing limits too frequently or too radically can destabilize the team. Making small, incremental changes and observing their effects is a healthier approach. For more agile learning and resources, visit our AgileKoc Learn page.

Artificial intelligence is revolutionizing the software development world and reshaping how Scrum teams operate. To succeed in this new era, teams must understand the new bottlenecks created by AI and adjust their Work-In-Progress (WIP) limits accordingly. This is not a one-and-done task but a journey requiring continuous observation, adaptation, and improvement.

As Scrum Masters and product leaders, it's up to you to support your team through this transformation. Consciously manage WIP limits to maximize the potential offered by AI while safeguarding your team's sustainability and well-being. Remember, agility is the ability to adapt to change, and this shift brought by AI is an excellent opportunity to flex your agile muscles.