Coding agents: Augment Code and AI-assisted DevOps

There are two camps regarding the implications of artificial intelligence. Some view the technology as a job usurper, while others see it as an augmenter. The latter philosophy is Augment Code’s raison d’être; the company firmly believes that coding agents drastically reduce time-to-code from days to hours, while freeing engineers to focus on higher-level decisions such as system architecture, maintainability and security.

Augment Code’s Guy Gur-Ari discusses AI coding agents with theCUBE.

Rather than removing humans from the loop, coding agents place them in a managerial role, curating output and guiding development, according to Guy Gur-Ari (pictured, right), co-founder of Augment Code.

“I’m one of the founders at Augment Code,” he said. “We work on developing an AI assistant for professional developers that works on large code bases, large teams for performing real software development tasks. To me, everything that’s happening now with large language models and code is just incredibly exciting.”

Gur-Ari spoke with theCUBE’s John Furrier alongside Howie Xu, chief AI innovation officer at Gen Digital Inc., at theCUBE + NYSE Wired: Robotics & AI Infrastructure Leaders 2025 event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed groundbreaking insights on how AI agents are transforming the way software is built, maintained and scaled.

AI coding agents elevate rather than replace devs

There’s been a recent trend where the code quality from AI agents has been assessed as on par with the junior developer level. These apples-to-oranges parallels miss the mark, according to Gur-Ari. While that assertion may be partly true — especially around architectural decisions — the value of coding agents lies in speed, breadth of knowledge and the agent’s ability to integrate with vast codebases and libraries.

“We’re not setting out to replace software engineers; we’re setting out to augment them and help them be more productive,” Gur-Ari said. “And that’s certainly what we’re seeing with the agent now. Things that used to take a developer hours, days or weeks to perform can now be done in hours or less. But to us, what that means is developers can ultimately then be more productive and produce more and build even more amazing products than they could before.”

Importantly, the success of these tools hinges on supervision. Left unchecked, agents can accrue technical debt quickly, according to Gur-Ari. But with the right oversight, they produce high-quality, scalable code quickly.

“I’ve been developing software for decades, and in the last few months, I’ve not had to write a line of code myself,” he said. “I use the agent to do all of the software development, and then I go and supervise what it does. That’s my day-to-day right now.”

The exciting times don’t stop at individual agents. Multi-agent collaboration is now emerging, where engineers can orchestrate several agents in parallel to tackle different parts of a system or explore multiple solution paths simultaneously, according to Gur-Ari.

“You can run multiple agents in parallel, working on different tasks, and then you no longer need to be concerned with the nitty-gritty details of every single line of code,” Gur-Ari said. “I think a lot of it becomes supervising the high-level decisions that the agents made and making sure that they’re correct.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of theCUBE + NYSE Wired: Robotics & AI Infrastructure Leaders 2025 event:

Photo: SiliconANGLE

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