The software development landscape is experiencing a profound transformation as AI agents increasingly take over coding tasks. For Scrum practitioners, this isn’t merely an evolution—it’s a revolution that demands immediate attention.

The Unfolding Crisis for Scrum Teams

Software development as we know it is facing extinction.

AI is not merely assisting developers—it’s replacing them at a breathtaking pace. Recent data reveals that Cursor alone is writing almost 1 billion lines of accepted code daily, representing a substantial percentage of all code created worldwide. This exponential growth in AI-generated code signals an existential threat to traditional Scrum teams and their well-established ways of working.

Meanwhile, organizations that cling to conventional Scrum face a stark reality: they’re falling behind competitors who embrace AI orchestration. The gap between AI-enabled teams and traditional teams isn’t incremental—it’s exponential. While traditional teams measure progress in story points and sprint velocity, AI-augmented teams are deploying features at rates previously thought impossible.

During their recent fireside chat at Llamicon 2025, Mark Zuckerberg and Satya Nadella confirmed what many have suspected: the AI transformation of development is happening faster than anyone predicted. Zuckerberg made a startling prediction:

“Our bet is sort of that in the next year probably, maybe half the development is going to be done by AI as opposed to people, and then that will just kind of increase from there.”

This isn’t just another technology cycle. It’s a fundamental reshaping of how software gets built.

The End of Traditional Software (and Scrum) as We Know It

The traditional three-role Scrum framework—Product Owner, Scrum Master, and Developer—was designed for human teams working with human dynamics and limitations. But what happens when most of your “developers” aren’t human at all?

Even more fundamentally, the very nature of software applications is being reimagined. As Nadella explained during the fireside chat, the traditional boundaries between applications like Word, Excel, and PowerPoint are dissolving in the AI era:

“In fact, the other thing we used to always think about is why are Word, Excel, PowerPoint different? Why isn’t it one thing? And we’ve tried multiple attempts of it. But now you can conceive of it, right, which is you can start in Word and you can sort of visualize things like Excel and present it, and they can all be persisted as one data structure.”

This transformation extends beyond Microsoft’s office suite. The entire concept of distinct applications is being challenged by a new paradigm where humans interact with AI agents rather than traditional software interfaces. As Nadella noted, these “artificial category boundaries” were created “mostly because of limitations of how our software worked.” The AI revolution enables a “malleability that was not as robust before.”

What emerges is a fundamental architecture change: databases containing ground truth, AI agents that can manipulate and present that data in whatever format humans need, and humans who orchestrate these agents through natural conversation rather than application-specific interfaces. In this world, traditional software applications become mere visualization layers for AI-processed information or disappear entirely.

Nadella highlighted this transformation:

“The entire technology stack needs to be rethought for the world of agents. How will agents write code, how will they retrieve things from a database? How will they browse the web? How will they talk to each other?”

These aren’t theoretical questions—they’re immediate challenges facing Scrum teams today.

As development work shifts to AI agents, the fundamental assumptions underlying Scrum ceremonies break down:

• Daily standups become obsolete when AI agents work 24/7 with perfect coordination
• Sprint planning changes when estimation becomes algorithmically precise
• Retrospectives transform when performance data is continuously analyzed by AI…

Clinging to traditional Scrum practices in this new environment isn’t just inefficient—it actively hampers an organization’s ability to leverage AI’s full potential.

What Tech Leaders Are Saying?

The conversations between Zuckerberg and Nadella reveal just how quickly this transformation is happening. At Microsoft, 20-30% of the code in some projects is already AI-written. Meta is aggressively pursuing AI that can perform machine learning engineering, effectively teaching AI to improve itself.

Nadella emphasized that we’re experiencing “multiple S-curves that compound” with AI development, creating exponential improvement every 6-12 months. This isn’t incremental change; it’s a reinvention of the entire software development paradigm.

Most telling was Zuckerberg’s vision of every software engineer becoming “more of like a tech lead in the future that has sort of their own little army of engineering agents that they work with.” This isn’t a distant future—it’s happening now.

Is the New Scrum – Humans as AI Orchestrators?

The survival of Scrum depends on a radical reimagining of roles. In this new paradigm, humans don’t disappear—they evolve into orchestrators of AI agent teams.

From Product Owner to Value Architect

In traditional Scrum, Product Owners spend considerable time managing backlogs, writing user stories, and prioritizing features. In the AI-augmented world, these tactical activities are increasingly automated. The new Product Owner—better described as a Value Architect—focuses on higher-order responsibilities:

Strategic Vision Translation

Value Architects translate business strategy into clear directives that AI agents can execute upon. Rather than writing detailed user stories, they focus on articulating the “why” behind features and defining success metrics that AI can optimize for.

Ethical Guardrails

As AI lacks inherent ethical judgment, Value Architects must establish clear ethical boundaries and ensure AI-developed solutions align with organizational values and societal norms.

Customer Insight Integration

While AI excels at data analysis, it struggles with a nuanced understanding of unspoken customer needs. Value Architects bring human empathy and market intuition to guide AI development in directions that data alone cannot reveal.

From Scrum Master to Agent Orchestration Coach

The traditional Scrum Master role focused on facilitation, removing impediments, and coaching teams on Scrum practices. The new Agent Orchestration Coach has a fundamentally different focus:

AI-Human Team Dynamics

As teams become hybrid collections of human specialists and AI agents, Orchestration Coaches establish effective collaboration patterns between humans and machines.

Workflow Optimization

Orchestration Coaches continuously refine how work flows between human decision-makers and AI implementers, ensuring smooth handoffs and maximum efficiency.

System Architecture Guidance

With complex networks of specialized AI agents working together, Orchestration Coaches help design the interactions between agents, preventing conflicts and optimizing overall system performance.

From Developer to Technical Director

Traditional developers who write code line by line are most directly affected by the AI revolution. Their evolution into Technical Directors represents the most profound shift:

AI Prompt Engineering

Technical Directors become expert prompt engineers, crafting precise instructions that guide AI agents to generate optimal code, tests, and documentation.

Quality Oversight

While AI generates code at unprecedented speeds, Technical Directors ensure this code meets architectural standards, security requirements, and performance benchmarks.

Domain Knowledge Integration

Technical Directors provide critical domain expertise that AI lacks, ensuring generated solutions address the unique needs of specific industries or problem domains.

How to Navigate the Transition?

Organizations facing this transformation need practical strategies to evolve their Scrum practices without disrupting ongoing delivery. Here’s how each role can begin the transition:

For Current Product Owners – Becoming Value Architects

Start with Strategy

Allocate more time to understanding business strategy and less to tactical backlog management. Define clear value metrics that can guide AI prioritization decisions.

Learn Prompt Engineering

Develop skills in writing clear, effective prompts that can guide AI agents toward desired outcomes. This is the new “user story writing” of the AI age.

Develop AI Literacy

Invest in understanding AI capabilities and limitations to make informed decisions about what tasks to delegate to agents versus what requires human judgment.

Download the Ultimate ChatGPT Prompt Ebook (2025 Edition)

For Current Scrum Masters – Becoming Orchestration Coaches

Study AI Workflow Patterns

Research emerging best practices for human-AI collaboration and begin experimenting with workflow optimization in your current teams.

Reconfigure Ceremonies

Start reimagining Scrum ceremonies to accommodate AI’s 24/7 work patterns and instantaneous communication capabilities.

Build Technology Fluency

Develop a deeper technical understanding of AI systems and their orchestration, moving beyond the purely facilitative aspects of traditional Scrum Master work.

For Current Developers – Becoming Technical Directors

Embrace Abstraction

Shift focus from writing implementation code to defining higher-level architectural patterns that can guide AI code generation.

Master AI Collaboration Tools

Invest time in learning platforms like GitHub Copilot, Replit, and other AI coding assistants to understand their capabilities and limitations.

Develop Systems Thinking

As Zuckerberg noted, systems thinking becomes more valuable than knowledge of specific programming languages. Study complex systems and how multiple agents can work together effectively.

The Path Forward is in Implementing AI-Augmented Scrum

Organizations ready to embrace this transformation should consider these practical steps:

Reimagine Ceremonies for the AI Age

Download the Ultimate ChatGPT Prompt Ebook (2025 Edition)

Continuous Planning

Replace rigid sprint planning with continuous planning processes where Value Architects set direction and AI agents dynamically adjust implementation details based on real-time feedback.

Asynchronous Coordination

Replace daily standups with asynchronous coordination systems where humans review AI progress and provide guidance through documented decisions rather than meetings.

Data-Driven Improvement

Transform retrospectives from scheduled meetings to continuous improvement systems driven by AI analysis of development metrics and automatic implementation of optimization strategies.

Create New Feedback Loops

Traditional Scrum thrives on tight feedback loops between developers and stakeholders. AI-augmented Scrum requires different feedback mechanisms:

AI Output Reviews

Establish regular reviews of AI-generated artifacts by human experts to validate quality and alignment with business goals.

Performance Dashboards

Create real-time dashboards that provide visibility into AI agent performance and work progress, enabling human orchestrators to make informed decisions.

Value Verification

Implement systematic approaches to verify that AI-created solutions deliver the expected business value, with clear metrics for success.

Develop New Team Structures

The composition of effective teams changes dramatically in the AI-augmented world:

Mixed-Capability Teams

Create teams that blend Value Architects, Orchestration Coaches, Technical Directors, and domain experts who can guide AI agents effectively.

Agent Specialists

Develop team members who specialize in specific types of AI agents, understanding their strengths, limitations, and optimal use cases.

Ethics Guardians

Designate team members responsible for ensuring AI outputs meet ethical standards and align with organizational values.

The Inevitable Transformation

The shift to AI-augmented Scrum isn’t optional—it’s inevitable. Organizations that embrace this transformation will gain unprecedented advantages in speed, quality, and adaptability.

As Nadella observed, “The question for us is in the next year, can we get—like, let’s take a kernel optimization—will we get to sort of something like that that happens? I think it’s more likely.”

The future of Scrum doesn’t eliminate humans; it elevates them. By shifting from implementation to orchestration, Scrum practitioners can deliver more value than ever before—harnessing AI’s computational power while providing the strategic direction and ethical guidance that only humans can offer.

The choice isn’t whether to make this transition—it’s how quickly and effectively you can embrace it before your competitors do.

Dejan Majkic, MA in CS &IT
Scrum Master, Product Owner, Teacher
www.whatisscrum.org/courses