Where Does GenAI Fit into the Modern Developer Stack?

Our workdays look a lot different than they used to.??

Coding used to mean writing every line from scratch, relying on just our skills to get things done. Now, with GenAI integrated into our workflows, we get help right from the start—suggesting code, filling in gaps, and even writing entire functions as we go. Not only is it helping us code more efficiently, but it’s also changing how we manage our entire workload. So, how exactly does GenAI fit into the modern developer stack, and where is it taking us next???

GenAI’s role in today’s workflow?

GenAI is already woven into our daily routines, quickly becoming a staple in the development process. Here’s where it’s making the most impact so far.???

• Coding assistance: GenAI tools like GitHub Copilot, Amazon CodeWhisperer, and ChatGPT offer real-time suggestions and even generate code. While it’s clear that these tools are helping us code faster and more efficiently, it’s important for us to make sure they’re giving us accurate outputs that are tailored for our specific needs.??

• Documentation generation: Creating documentation has become much easier with GenAI. It can auto-generate code comments and API docs, and even guides us as we code. While not always part of the DevOps loop, documentation is essential for clarity and maintainability, especially in large organizations. By automating the process, we have more time to focus on strategic work.??

• Infrastructure automation: In infrastructure management, GenAI takes on some of the heavy lifting by simplifying script creation for tools like Ansible and Terraform. It also supports virtual testing by simulating network loads, cutting down on the need for extensive physical setups.?

• Security enhancement: GenAI strengthens security efforts by detecting patterns, analyzing traffic, and identifying potential threats. Implementing AI guardrails helps ensure safe operations, particularly when handling sensitive API interactions.??

Where will it take us next???

This is just the beginning. GenAI is opening up new possibilities that could fundamentally change the way we work. We’re still in the early days of this journey, but the impact is already showing in a few key areas.??

• API management: Managing how different systems communicate has become more complicated as we've began to use more APIs. Especially with the shift to cloud-native environments, breaking down large applications into smaller, containerized components has led to API sprawl, and every interaction between these components now relies on an API call. GenAI helps by simplifying these interactions, organizing and streamlining the flow of data between systems. It also helps ensure that those connections are secure.??

• Testing automation: GenAI is also beginning to shine in testing. It can automate unit tests and generate functional code and documentation, so we can focus more on solving problems and less on manual testing.?

• Infrastructure as Code: It’s helping with script-building for automation, supports virtual testing before physical deployment, and enables synthetic traffic generation, which is important for wireless tech and network load testing.??

• Advanced code review: GenAI is making code reviews smarter and more thorough, improving test frameworks and giving us more confidence when pushing code to QA or production.?

Let’s make the most of GenAI?

It’s clear that GenAI is going to keep evolving, bringing even more benefits to our work. As it does, we need to make sure we’re using it in the best way possible.??

To learn more about how GenAI is shaping DevOps and how it can help you work smarter, check out our latest article from Shannon McFarland (VP, Cisco DevNet) and Matt DeNapoli , (Head of Developer Strategy & Product Management, Cisco DevNet).??

And we’d love to hear from you—what’s the biggest difference #GenAI has made in your work so far???