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Eligiblethe $1.5 billion cloud content governance company, has integrated AI coding tools into its global team of more than 350 developers, but without reducing headcount. Instead, the company continues to hire junior engineers, using AI to speed up onboarding, deepen understanding of the codebase, and shorten the path from junior to senior contributor.
This approach challenges the prevailing idea by 2025 that automation will replace developers, instead showing how companies are using AI to scale their engineering capabilities while keeping humans firmly in the loop.
“The disappearance of engineers or us not hiring junior engineers does not seem to be the likely outcome,” Amrit Jassal, CTO and co-founder of Egnyte, told VentureBeat. “You have to have staff, train and plan all kinds of successions. Today’s junior engineer is tomorrow’s senior engineer.”
How Egnyte Coders Use AI — Without Giving Up Control
Egnyte, which has over 22,000 users including NASDAQ, Red Bull and BuzzFeed, has deployed Claude Code, Cursor, Augmentation and Gemini CLI coding tools within its developer base to support its core business strategies and expand its new AI offerings, such as customer-facing co-pilots and customizable AI agents.
Developers use these tools for a variety of tasks, the simplest of which include data retrieval, code understanding, intelligent searching, and code searching. Egnyte’s codebase contains a lot of Java code, which uses many libraries, each with different versions, Jassal explained. AI tools are perfect for peer-to-peer programminghelping new users get the lay of the land, or existing users explore different code repositories.
“We have a pretty large code base, right? » said Jassal. “Let’s say you’re looking at an iOS app, but you’re not very proficient; you’ll run Google CLI or an Augment and ask it to discover the code base.”
Some Egnyte developers are turning to automatic pull request summaries, which provide simple overviews of code changes that essentially explain the “what,” “how,” and “why” of the proposed changes.
“But obviously, for any change we make, we don’t want to hear that the AI made the change; it has to be the developer who made the change,” Jassal stressed. “I wouldn’t trust AI to engage with the production code base.”
Commits always go through human review and security validationand any alarm signals are relayed to senior engineers. Developers are warned of the dangers of settling into autopilot mode or blindly trusting the code. A model may not have been exposed to certain coding components and frameworks or may not have received enough samples during training.
Another growing and closely watched use case for AI is unit testing, in which components of code are executed in isolation to ensure they work as expected. “Ultimately, it’s a productivity-enhancing tool,” he said. “It’s really a continuation, it’s like any other tool, it’s not magic.”
Beyond basic engineering, AI helps other teams collaborate with programmers. Product management, for example, uses tools like Vercel to deliver “demo-worthy” prototypes, rather than just ideas, to developers, who can then move forward with mockups. Or, if UX teams are looking to change certain elements of a dashboard, AI can quickly suggest a handful of options, like different widgets or buttons.
“Then you come to engineering with that, and the engineer immediately knows what you actually intend to do with it,” Jassal said.
Set expectations, meet developers where they are
However, the daily activities of all Egnyte engineers, including junior developers, go beyond simple 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 phases of software engineering, as well as deployment, production and post-deployment maintenance.
In turn, these activities require “Egnyte-specific tacit knowledge and experience” provided by senior engineers. A clear example of work that falls closely to senior engineers is writing architecture notes, because these span the entire platform and require a more holistic system-level view, Jassal said.
“Nowadays, many traditional obstacles are overcome faster with AI; for example, understanding the code base, analyzing requirements, automatic testing,” he said. “This faster path allows our talented young recruits to progress more quickly and bring higher value to the company more quickly.”
The company expects a much faster learning curve from entry-level to mid-level engineers, Jassal said. “It’s always the case that people who come straight into the workforce are a lot more enthusiastic about trying new things,” Jassal said. But this must be tinged with reality to temper expectations, he added.
On the other hand, some experienced engineers may need to accelerate their adoption because they are hesitant or have had poor or poor experiences with previous generation tools. This requires a gradual introduction.
“Senior officials, who have been burned repeatedly, bring this point of view,” he said. "So both [types of engineers] play an important role. »
Recruitment will continue for reasons of scale and new perspectives
“In general, I would say it’s been very hyped by people who want to sell you tokens,” Jassal said, referring to people talking about the obsolescence of human coders.
"Vibrational coding" could be interpreted in the same vein: like others in software development, he prefers the term “AI-assisted coding”, in which programmers have a self-driving loop, generating code, analyzing exceptions, then fixing and scaling.
At least in Egnyte’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 to scale, but 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 engineering jobs, but that it will reshape how talent is developed.
At Egnyte, AI-assisted coding reduces learning curves and increases expectations, without removing humans from the process. Companies that view AI as a substitute risk emptying their future senior talent pool; those who treat it like infrastructure can scale more quickly without losing the judgment, creativity, and accountability that only engineers can bring.
