AI is dramatically increasing developer productivity, but many companies are struggling to translate those gains into measurable business outcomes. In a TechVoices interview, GitLab Chief Product and Marketing Officer Manav Khurana explained that AI-assisted coding is creating unprecedented speed, but also introducing new issues around reliability, security, governance, infrastructure scale, and cost control.
He outlined GitLab’s approach to the agentic engineering era, including Orbit, a lifecycle context graph designed to give AI agents better enterprise context, along with new governance and platform controls intended to help companies gain agentic speed without losing enterprise oversight.
Core Takeaways
Developer Productivity Gap: AI tools are helping developers move faster, but enterprises are not always seeing the same gains because AI-generated work can create reliability, security, governance, and cost challenges.
Context Is Critical: GitLab Orbit creates a digital twin of the software environment, giving AI agents richer context so they can work faster, use fewer tokens, and produce more accurate results.
Enterprise Control Layer: GitLab positions its platform as a gatekeeper between AI agents and enterprise code, enforcing permissions, policies, audit trails, and human-in-the-loop controls.
Developers Still Matter: Khurana argues that AI will change the developer role, but not eliminate it, because humans will be needed for architecture, design, orchestration, governance, and customer-value decisions.
Key Quotes
The Productivity Paradox
“When we survey our customers, survey developers, we’re finding 90% plus of developers are using two or more tools, reporting much higher productivity and speed in their daily jobs. In fact, we’ve seen our customer code bases grow as much as five times over a year.”
“But that speed is also bringing chaos. We see the chaos in terms of reliability incidents in the industry or security incidents in the industry or agents hallucinating and showing up with artificial confidence. And that leaves it on all of us to then figure out where did the agents go wrong?”
Orbit and the Power of Context
“Orbit is a digital twin of a GitLab instance that has all the relevant information stitched together. So instead of doing 200,000 lookups, you do one lookup and all the relationships are available right away.”
“There’s an adage in the AI world, which is AI agents work as well as the context that they’re given. This is really about that context component that we are fixing.”
GitLab as the AI Gatekeeper
“When an agent wants to read a code base, it must go through GitLab. When an agent has to write to a code base, it must go through GitLab.”
“Because we sit in the middle as the gatekeeper, that’s why we are able to provide that level of control.”
The Future Developer Role
“It is absolutely true that the role of a developer and a software engineer is changing because a lot of the code writing and a lot of the tasks are being done with the help of agents and we can go a lot faster.”
“But I only see the need for developers and software engineers grow because now there are even more architecture decisions to be made. There are even more design decisions to be made. There are even more customer value decisions to be made than ever before.”
