Eligiblethe $1.5 billion cloud content management company has embedded AI coding tools into its global team of more than 350 developers, but not to reduce its workforce. Instead, the company continues to hire junior engineers, using AI to accelerate onboarding, deepen understanding of the codebase, and shorten the path from junior to senior contributor.
This approach challenges the dominant 2025 narrative that automation will replace developers, and instead shows how companies are using AI to scale technical capacity while keeping humans informed.
“It doesn’t seem like a likely outcome that engineers will disappear or that we won’t hire junior engineers,” Amrit Jassal, CTO and co-founder of Egnyte, told VentureBeat. “You have to have people, you train and do all kinds of succession planning. The junior engineer of today is the senior engineer of tomorrow.”
How Egnyte coders use AI – without giving up control
Egnyte – which has more than 22,000 users, including NASDAQ, Red Bull and BuzzFeed – has been rolled out Claude Code, Cursor, Augment and Gemini CLI coding tools across the developer base to support key business strategies and extend newer AI offerings such as customer-facing copilots and customizable AI agents.
Developers use these tools for a variety of tasks, the simplest of which include data retrieval, code understanding, smart searching, and code lookup. Egnyte’s code base contains a lot of Java code, which uses numerous libraries, each with different versions, Jassal explains. AI tools are great for peer-to-peer programming, helping new users understand the terrain or allowing existing users to explore different code repositories.
“We have a pretty big code base, right?” Jassal said. “Say you’re looking at an iOS application, but you’re not well versed; you launch Google CLI or an Augment and ask it to discover the code base.”
Some Egnyte developers are moving to automatic pull request summaries, which provide simple overviews of code changes that essentially explain the “what,” “how,” and “why” of proposed changes.
“But obviously for every change that is made, we don’t want to hear that AI made the change; it has to be the developer that made the change,” Jassal points out. “I wouldn’t trust AI to commit to the production code base.”
Commitments continue to undergo human review and security validation, and anything red flagged will be escalated to senior engineers. Developers are warned about the dangers of going on autopilot or blindly trusting code. A model may not have been exposed to or given sufficient examples of certain coding components and infrastructure during its training.
Another growing and closely monitored use case for AI is unit testing, where code components are run in isolation to ensure they work as intended. “Ultimately it is a productivity improvement tool,” he said. “It’s really a continuation, it’s just like any other tool, it’s not magic.”
In addition to core engineering, AI helps other teams collaborate with programmers. For example, product management uses tools like Vercel to bring “demo-worthy” prototypes, rather than just ideas, to developers, who can then move on to mock-ups. Or, if UX teams want to change certain elements on a dashboard, AI can quickly display a handful of options, such as different widgets or buttons.
“Then you end up in technology, and the engineer immediately knows what you really intend to do with it,” says Jassal.
Setting expectations, meeting developers where they are
However, the daily activities of all Egnyte engineers, including junior developers, extend beyond coding.
Junior developers are given hands-on tasks throughout the development lifecycle to accelerate their growth and experience, Jassal said. For example, they help with requirements analysis in the early software engineering phases, as well as in implementation, productization, and post-deployment maintenance.
These activities in turn require “Egnyte-specific tacit knowledge and experience” offered by senior engineers. A clear example of work that suits senior engineers is writing architecture notes, as these cut across the entire platform and require a more holistic view at the system level, Jassal said.
“Many of the traditional roadblocks today are navigated more quickly with AI; for example, understanding the codebase, parsing requirements and testing automatically,” he said. “This accelerated path allows our talented junior associates to progress faster and add value to the business sooner.”
The company expects a much faster learning curve from junior to mid-level engineers, Jassal said. “It’s always the case that people who come straight into the workforce are much more enthusiastic about trying new things,” says Jassal. But that needs to be colored with reality to temper expectations, he added.
On the other hand, some senior engineers may need to ramp up their adoption because they are hesitant or have had bad experiences with previous generation tools. This requires a step-by-step introduction.
“The seniors, who have been burned multiple times, bring that perspective,” he said. ‘So both [types of engineers] play an important role.”
Hiring will continue for scale and a new perspective
“Overall, I would say it’s really hyped by people wanting to sell you tokens,” Jassal said, referring to people talking about human coders becoming obsolete.
“Vibe coding” could be interpreted similarly: Like others in software development, he prefers the term “AI-assisted coding,” where programmers have a self-directed loop, generating code, analyzing exceptions, and then correcting and scaling.
At least in Egnyte’s case, hiring will continue, even if at a slower pace as people become more productive thanks to AI, Jassal said.
“We are recruiting not just for scale, but also to develop the next generation of senior developers and inject new perspectives into our development practices,” he said.
The takeaway for tech decision makers is not that AI will eliminate tech jobs, but that it will reshape the way talent is developed.
At Egnyte, AI-assisted coding compresses learning curves and increases expectations, without removing people from the process. Companies that look at AI as a replacement risk eroding their future senior talent pipeline; those who view it as infrastructure can move faster without losing the judgment, creativity, and responsibility that only engineers provide.
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