Collaborative Systems Over Individual Productivity

Since the early 2000s, I’ve been navigating the complexities of global software delivery, leading teams spread across continents and time zones. Back then, transitioning from traditional waterfall methods to agile and hybrid models was a challenge, but with time, we developed global delivery models and processes that allowed us to be more efficient and productive.

Fast forward to today, as we grapple with new advancements like GenAI in software delivery, one of the most common questions I hear is, 'Will GenAI boost productivity and streamline global delivery?'

It’s a question that taps into the heart of every tech-driven organization—how can we make things faster, smarter, and better?

But as tempting as the promise of speed and automation might be, I can’t help but step back and take a deeper look.

What if the key to better software delivery isn’t found in boosting individual productivity? What if it’s in how we collaborate as teams?

In my experience, focusing solely on individual productivity overlooks the bigger picture. Global software delivery isn’t about individual wins; it’s about how teams collaborate across geographies to work as a cohesive unit.

Global Delivery: A Team Sport, Not a Race

Software development is a curious thing. On the surface, it might seem like a straightforward pipeline—a developer writes code, it gets tested, and eventually, it gets shipped. But, like most complex systems, it doesn’t quite work that way. The real engine behind software delivery isn’t the individual lines of code; it’s the collective efforts of a team. It’s a system.

When I think about software delivery at a global scale, the image that comes to mind isn’t a sprint—it’s more like a relay race.

You can’t simply hand off the baton and expect everything to go smoothly. Every link in the chain depends on the one before it.

I remember the first time I worked in a large development team. I quickly realized that success wasn’t measured by how fast I could code or how polished my contributions were. Instead, it was about how well we, as a team, could work together. How seamlessly our ideas flowed, how efficiently we caught and resolved issues, and how we navigated the inevitable roadblocks that cropped up.

The idea of introducing GenAI into this system is both exciting and daunting. What would happen if one part of the team suddenly became 50% more productive? Would it create bottlenecks elsewhere? While GenAI has the potential to enhance productivity, it must be applied thoughtfully within the larger framework of collaboration.

That is where true efficiency and innovation happen, in the space where teams collaborate seamlessly across regions and systems.

The Trap of Focusing on Speed

Imagine this: you’ve got a new GenAI assistant, and suddenly your team’s developers are coding 50% faster. It sounds fantastic, right? But what happens to the rest of the process? Can your testers, your project managers, and your infrastructure handle this new velocity?

This reminds me of a story about a company that implemented a new system to speed up its packaging process. They went from packing 100 units an hour to 200. But instead of celebrating, they hit a wall. Their shipping department couldn’t keep up, leading to massive bottlenecks. The result? No one felt the benefits of their shiny new system. This kind of scenario isn’t entirely hypothetical.

In global software delivery, a similar ripple effect can occur. Speeding up coding alone doesn’t guarantee faster delivery—it can sometimes backfire by introducing technical debt, creating bottlenecks in testing, or overwhelming project management and infrastructure support.

GenAI has immense potential, but it’s not a silver bullet. A boost in individual productivity without a focus on the overall system might leave you with more problems than solutions.

Some delivery methodologies must adapt to accommodate GenAI. For example, GenAI can enhance productivity at various stages such as Strategy & Planning, Design, Coding, Testing, and Production Release

This is what I realized: focusing on individual productivity without considering the global system as a whole can backfire. Speeding up one part of the chain often slows down another. It’s not just about how fast code gets written—it’s about how well the entire process flows, from start to finish, across multiple regions.

Global Engineering: Principles Matter More Than Ever

Solid engineering practices are the glue that holds global teams together. With AI amplifying certain tasks, these principles become more crucial than ever. GenAI can support developers, but it’s not a substitute for the hands-on experience and depth of understanding that comes from solving complex problems firsthand.

When I think about the role of AI in software development, I see it as a partner—a tool that can assist, not replace. There’s a real risk in relying too heavily on AI-generated code without understanding the reasoning behind it. Developers could spend more time correcting AI errors or, worse, they might lose the hands-on experience that’s essential for growth. Over time, this could lead to bad habits, or even worse, to a generation of developers who are skilled at managing AI but lack the depth of understanding needed to solve tough problems independently.

In distributed teams spread across the globe, these engineering practices become even more critical. For instance: Documentation needs to be impeccable. Communication needs to be crystal clear. And perhaps most importantly, every team needs to feel empowered to collaborate, not just to code.

This means ensuring that the AI is accessible to all teams, regardless of location. What worked for our U.S. team needed to be just as effective for our developers in Latin America or Asia. It isn't enough to improve individual productivity—we had to enhance collaboration at every level.

Good software delivery is about balance. GenAI can support teams, but it needs to be woven into a system that values collaboration and learning, not just speed.

A System-Wide Approach

As organizations continue exploring AI’s role in software delivery, I believe we need to think bigger.

We shouldn’t ask, “How can this tool help us work faster?” Instead, we should ask, “How can this tool help us work better—together?”

The future of software development isn’t about creating faster coders; it’s about building stronger teams. And GenAI, when used thoughtfully, can be part of that bigger picture. But it’s not about replacing human skills or turning coding into an isolated task. It’s about enhancing the collaborative system that is, and always will be, the heart of effective software delivery.

I prefer a global delivery model where GenAI helps teams hand off work more seamlessly across borders. Where documentation is automatically generated, making sure every region has the context they need to pick up where another left off. Where the challenges of operating across multiple time zones feel less daunting because the system itself is designed to support collaboration, not just speed.

In an increasingly interconnected world, GenAI’s true potential isn’t in enhancing individual efficiency, but in transforming how we work together across borders. By fostering seamless collaboration and supporting stronger systems, GenAI can unlock a new era of global software delivery.

And for me, that’s where the real magic happens.