How AI Is Changing Software Teams, with Stephen Wooten

What happens when AI becomes part of how software teams build every day? For engineering leaders, the answer goes beyond writing code faster. 

While AI can help teams write code, test ideas, and move with less friction, it also raises new questions around priorities, product judgment, team structure, and how companies help people use these tools well.

In this episode, Marcelo sat down with Stephen Wooten to talk about how AI is shaping software development, where companies are getting adoption wrong, and why engineering teams need to think beyond code.

Meet Stephen Wooten: Building and Leading Engineering Teams

Stephen Wooten is an engineering leader with nearly 2 decades of experience across software entrepreneurship, product development, and team building.

He started programming in high school and college, before moving into web development through his own startup. Since then, his career has taken him from early-stage companies to larger organizations like Groupon. 

He was also a co-founder at Kin Insurance, and today works as VP of Engineering at a stealth company focused on financial auditing services.

When AI Becomes Part Of The Team

The conversation covered how AI is changing software teams, from daily workflows to hiring, product decisions, and company culture.

🎧 If you’d prefer to hear the full discussion, the podcast episode is available below. Otherwise, keep reading for a recap of the highlights.

Using AI Across The Whole Company

Stephen opens up the conversion explaining that AI shouldn’t be treated only as an engineering tool. As he explains, the goal at the company he works in, is to help everyone learn how to prompt LLMs and think about how AI can fit into their workflows.

As he puts it, this comes with a shift in how people understand their own role and value.

“You need to decouple yourself from being the one who does the task, to being the one who designs the process.”

That mindset also shapes how the company introduces people to AI from day one. As an example, Stephen’s team built an AI-powered onboarding skill to make the process smoother.

Where Companies Get AI Wrong

Stephen sees many companies making the same mistake of buying an AI tool and assuming that means they are using AI well.

In engineering, that can mean giving teams access to tools like Copilot or Cursor while keeping the same habits and processes underneath.

“You’ll hear AI-assisted coding, and that’s just kind of dipping your toe in the waters.”

For Stephen, real adoption requires more than adding AI to the stack. Companies need to help people rethink how they use it, where it fits, and what kind of work it should actually change.

The Risk Of Shipping The Wrong Things Faster

One of Stephen’s clearest points is that AI can make it easier for teams to build the wrong things faster.

As the cost of building goes down, more ideas start to feel possible, and that’s why companies may feel more tempted to say yes to things.

For Stephen, this makes prioritization more important than before. Teams need to be more disciplined and selective.

“Who cares how fast you move if you’re moving in entirely the wrong direction?”

Why Developers Need More Product Thinking

AI makes code easier to produce, so understanding what should be built becomes more important. 

Stephen argues that strong engineers aren’t just the ones who can complete a ticket. They also need to understand the product, question requirements when needed, and think about the business behind the work.

“If a product manager gave you requirements for a feature that didn’t make sense and you didn’t push back on it, then you’re building the wrong thing.”

For him, areas like product, engineering, and design can’t stay disconnected.

Can AI Help Startups Survive, Or Fail Faster?

Stephen’s take is that AI is powerful, but not automatically positive.

“I view AI as a tool almost like fire.”

The comparison reflects how fire can keep you warm and cook your food when used well, while it can burn down your house when used poorly.

The same applies to startups. AI can help small teams move faster and do more with less, but without clear priorities, it can also make mistakes happen faster.

How Companies Should Start Using AI

When it comes to getting started with AI, Stephen’s advice is to use it in more daily contexts, not just for work or code.

He mentions simple examples like planning a trip itinerary or using AI to find time on your calendar. Those everyday uses help people see where the tool helps and where they still need to think for themselves.

“Learn the edges of what AI can do well and what it doesn’t do well.”

Once people understand those limits, they can apply the tool more effectively in professional settings.