By Sabrina Farmer, CTO, GitLab

As I stepped into the role of Chief Technology Officer at GitLab earlier this year, I revisited one of my favorite books Trillion Dollar Coach. This leadership classic, free from corporate jargon, offers practical insights and was a reassuring reminder of the lessons and values I wanted to bring to my new role. 

The book focuses on former football player and coach Bill Campbell, who became a tech executive and leadership mentor to some of the tech industry's most successful entrepreneurs. One particular motto from Coach Bill, as he was known, stood out for me: "Work the team, then the problem." For him, it meant that a leader should form high-performing teams and give them the resources and freedom to do great things.

As we navigate the evolving landscape of DevSecOps and the transformative power of AI, this philosophy resonates with me. By building strong teams and empowering them to innovate, we can drive success in the face of complexity. 

AI Does Not Replace Strategic Work

Most DevSecOps teams aim to achieve a short time-to-deployment for high-quality software that solves business problems and increases revenue. However, in my experience, too many organizations focus on developer productivity without considering the developer experience. In other words, they've got talented developers focused on time-consuming, mundane, and repetitive tasks, and they perform that work under crushing deadline pressures. While those tasks can be counted, limiting an engineer's productivity measurement to that kind of work can be very demoralizing. 

The good news is that the smart use of AI can remove a great deal of friction from the software delivery process by taking over some of the least appealing work. This speeds up deployment cycles, improves code's security and quality, and improves developer morale. 

For example, AI can suggest or autocomplete code as the developer is working, create and perform various tests, or automatically document code functionality in a predetermined standard format for them, all of which would otherwise consume much of the developer's day. 

All these opportunities equate to a better developer experience. DevSecOps has always been about automation, so why not automate the tasks that team members find less appealing?

According to the more than 5,000 software development respondents polled for GitLab's 2024 Global DevSecOps Report, this shift is underway. They report that AI and machine learning (ML) are becoming well-established in software development workflows. Less than a quarter of respondents spend their time writing new code, with the rest spent in meetings and on administrative tasks, improving existing code, testing, and identifying and mitigating security vulnerabilities. That represents over 75% of developers' day-to-day tasks, where AI can introduce efficiencies.

When AI takes the strain, humans can focus on what they do best: critical thinking, problem-solving, and creative innovation. Engineers love tackling big, challenging projects that test their problem-solving skills. Why not let them concentrate their time on these? 

Time For Upskilling

When organizations get intentional with their deployment of AI, they can also create significant upskilling opportunities for ambitious developers seeking career advancement. Not only does it give them back valuable time, energy, and focus to spend on developing new skills, but it can also act as an outstanding coach to them-just like Bill Campbell. 

For example, AI can impart valuable lessons on optimizing code to be faster, understanding how existing code can be better structured, and identifying and remediating vulnerabilities long before code is deployed. Developers might use AI to learn or to reacquaint themselves with unfamiliar code bases, languages, and frameworks. 

A 2023 report from global strategy firm McKinsey finds that developers using generative AI-based tools in their work are more than twice as likely to report overall happiness, fulfillment, and a ‘state of flow' than their peers who don't have access to these tools. According to the report's authors, "They attributed this to the tools' ability to automate grunt work that kept them from more satisfying tasks and to put information at their fingertips faster than a search for solutions across different online platforms." 

These are the developers that every organization wants to hire and to keep on their team, the kind that Bill Campbell described as having "smarts and hearts." And that's the kind of developer experience that every engineering leader should aim to deliver. 

Campbell's relentless focus on building strong team and empowering talented individuals aligns perfectly with the modern DevSecOps landscape. By providing the right tools and fostering a positive work environment, we can attract, retain, and inspire top tech talent. 

AI emerges as a powerful catalyst in this equation. By automating routine tasks and augmenting human capabilities, AI can streamline workflows, enhance security, and accelerate innovation. Ultimately, it empowers teams to deliver exceptional software, driving business success and individual satisfaction.

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ABOUT THE AUTHOR

Sabrina Farmer is the Chief Technology Officer at GitLab, where she leads software engineering, operations, and customer support teams to execute the company's technical vision and strategy and oversee the development and delivery of GitLab's products and services. Prior to GitLab, Sabrina spent nearly two decades at Google, where she most recently served as vice president of engineering, core infrastructure. During her tenure with Google, she was directly responsible for the reliability, performance, and efficiency of all of Google's billion-user products and infrastructure. A long-time advocate for women in technology, Farmer earned a B.S. in Computer Science at the University of New Orleans, where she established two scholarships to help level the playing field for inclusion and empowerment in technology.