Egnite, a $1.5 billion cloud content governance company, has embedded AI coding tools into its global team of more than 350 developers — but not to reduce headcount. Instead, the company continues to hire junior engineers, using AI to accelerate onboarding, deepen codebase understanding, and shorten the path from junior to senior contributor.
This approach challenges a dominant narrative of 2025 that automation will replace developers, instead showing how enterprises are using AI to enhance engineering capability while keeping humans firmly in the loop.
“Engineers disappearing or us not hiring junior engineers doesn’t seem like a likely outcome,” Egnite CTO and co-founder Amrit Jassal told VentureBeat. “You have to have people, you’re training and making all kinds of succession plans. Today’s junior engineer is tomorrow’s senior engineer.”
How Egnyte coders are using AI – without giving up control
Egnyte – which has more than 22,000 users including NASDAQ, Red Bull and BuzzFeed – has launched Cloud Code, Cursor, Augment and Gemini CLI Coding tools across its developer base to support its core business strategies and expand new AI offerings like customer-facing co-pilots and customizable AI agents.
Dave uses these tools for a variety of tasks, the simplest of which include data retrieval, code understanding, smart search, and code lookups. Egnite’s code base contains a lot of Java code, which uses multiple libraries, each of which has different versions, Jassal explained. AI tools are great for peer-to-peer programming, helping new users get off the ground, or helping existing users check out different code repositories.
“We have a huge code base, right?” Jasal said. “Let’s say you’re looking at an iOS application, but you’re not well-versed; you’ll fire up the Google CLI or Augment, and ask it to find the code base.”
Some Egnite devs are moving towards automated pull request summaries, which provide a simple overview of code changes that essentially explain the “what,” “how,” and “why” of the proposed modifications.
“But obviously, any change that is made, we don’t want to hear that the AI made the change; it should be that the developer made the change,” Jassal explained. “I wouldn’t trust AI for a production code base.”
Commitments still undergo human review and security verification, and anything red flagged is escalated to senior engineers. Developers are warned about the dangers of settling into autopilot mode or blindly trusting code. A model may not have been exposed to certain coding components and infrastructure in its training, or may not have been given enough samples.
Another growing and closely monitored use case for AI is unit testing, where code components are run individually to ensure that they work as intended. “Ultimately, it is a productivity improvement tool,” he said. “It’s really a continuum, it’s like any other tool, it’s not magic.”
Beyond core engineering, AI is helping other teams collaborate with programmers. Product management, for example, is using tools like Vercel to bring “demo-worthy” prototypes rather than just ideas to developers, who can then proceed with mock-ups. Or, if UX teams are looking to change certain elements on the dashboard, the AI can quickly spin up a handful of options, like different widgets or buttons.
“Then you come into engineering with it, and the engineer knows right away exactly what you intend to do with it,” Jassel said.
Setting expectations, meeting developers where they are
However, day-to-day activities extend beyond just coding for all Egnite engineers, including junior developers.
Junior developers are given practical assignments across the full development lifecycle to accelerate their growth and experience, Jassal said. For example, they assist in requirements analysis in the early software engineering stages as well as deployment, productization, and post-deployment maintenance.
In turn, these activities require “Agnite-specific tacit knowledge and experience” brought to bear by senior engineers. An obvious example of work that sits strongly with senior engineers is writing architecture notes, Jassal said, because these cut across platforms and require a more holistic, system-level view.
“Many traditional barriers are increasingly overcome with AI these days; for example, understanding the codebase, analyzing requirements, auto-testing,” he said. “This fast track allows our talented junior employees to progress more quickly and provide higher value to the company sooner.”
The company expects junior to mid-level engineers to learn very quickly, Jassal said. “It’s always been the case that people coming straight into the workforce are more excited to try new things,” Jassal said. But to control expectations, it has to be tempered with reality, he said.
On the other hand, some senior engineers may need to accelerate their usage because they are hesitant or have had poor experience with previous generation tools. This requires a gradual introduction.
“Seniors who have been burned many times bring perspective,” he said. "so both [types of engineers] Play an important role.”
Hiring will continue for scale and new perspective
“In general, I would say it’s really been promoted by people who want to sell you tokens,” Jassel said, referring to those who talk about human coders becoming obsolete.
"vibe coding" Can be understood in a similar way: like others in software development, he prefers the term “AI assisted coding”, in which the programmer has a self-powered loop generating code, analyzing exceptions, then correcting and scaling.
At least in Egnite’s case, hiring will continue, albeit at a slower pace, as people become more productive thanks to AI, Jassal said.
“We’re not just hiring for scale, but also to grow the next generation of senior developers and incorporate new perspectives into our development practices,” he said.
The takeaway for tech decision makers is not that AI will eliminate engineering jobs – but rather that it will reshape the way talent is developed.
At Egnite, AI-assisted coding is slowing down the learning curve and raising expectations, not removing humans from the process. Enterprises that treat AI as a replacement risk hollowing out their future senior talent pipeline; Those who treat it as infrastructure can move forward faster without losing the judgment, creativity and accountability that only engineers provide.
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