Context is King, and Scrum Can Help

For years we've heard the phrase “content is king.” And while content is still important, I think it's time to crown a new king.

Today, I think it's fair to say that context is king.

Why Context is King

AI is powerful, but it only works well when it has the right context. Anyone who has experimented with AI tools quickly learns that the quality of the result depends heavily on the quality of the prompt. A weak prompt might simply ask a question, while a strong prompt explains the problem, the situation, and the desired outcome (not unlike the user story format). When AI understands not just what you want but also why you want it, the results are far more useful.

Organizations are recognizing this. For example, NTT DATA announced a global generative AI training initiative that seeks to provide foundational AI training for its roughly 200,000 employees worldwide. The goal is to help employees apply AI tools to real business problems, not just experiment with the technology.

This reflects an important reality: getting value from AI isn’t just about the tools. It’s about providing the context those tools need to produce meaningful results.

But AI is not the only place where context matters.

Scrum teams have understood this for years. That’s why we have a Product Goal, and why the user story format is so popular. Understanding why helps teams get a better handle on the business problem and make better decisions about how to solve it.

Chasing Tech is not the same as adding value

Without context, it’s easy to start chasing technology instead of solving problems.

I recently interviewed Siva Balu of Quartz Health Solutions, who will be the keynote speaker at this year's Scrum Day Madison conference. Here is what he had to say about chasing tech:

"When you chase tech, it is not going to pan out. But if you can identify the critical business problems and we apply the technology and the data to solve the business problems... those investments have been successful."— Siva Balu

AI can be a wonderful, time-saving tool. But without a clear business problem to solve, it can be too easy to spend a lot of time “chasing tech” as Siva says.

Here's how Scrum can help

AI is exciting. Like any powerful technology, it’s easy to become fascinated with what it can do.

But Scrum helps keep teams grounded.

Scrum forces regular conversations about value. Sprint Reviews bring stakeholders and developers together to inspect progress and discuss what actually solves customer problems.

A Sprint Review should not be just a demo. It should be a collaboration session where the team and stakeholders inspect what was delivered and discuss what to do next.

Scrum also encourages teams to deliver a done, usable increment every Sprint. This forces the team to test whether what they built actually solves a real problem instead of simply building more technology.

These practices reinforce the three pillars of Scrum: transparency, inspection, and adaptation. They help ensure the team continually checks whether their work is actually solving the right problem. This prevents teams from simply chasing the latest technology trend.

Instead, the focus remains on solving real-world problems. Those problems — the customer needs, the constraints, and the environment — are the context that allows teams to build the right solutions.

Because in the age of AI, context is king.