Egnyte, the $1.5 billion cloud content material governance firm, has embedded AI coding instruments throughout its international crew of greater than 350 builders — however to not cut back headcount. As an alternative, the corporate continues to rent junior engineers, utilizing AI to speed up onboarding, deepen codebase understanding, and shorten the trail from junior to senior contributor.
The method challenges a dominant 2025 narrative that automation will substitute builders, exhibiting as a substitute how enterprises are utilizing AI to scale engineering capability whereas maintaining people firmly within the loop.
“To have engineers disappear or us not hiring junior engineers doesn't look like the likely outcome,” Amrit Jassal, Egnyte CTO and co-founder, instructed VentureBeat. “You've got to have people, you're training and doing all types of succession planning. The junior engineer of today is the senior engineer of tomorrow.”
How Egnyte coders are utilizing AI — with out ceding management
Egnyte — which has greater than 22,000 customers together with NASDAQ, Purple Bull, and BuzzFeed — has rolled out Claude Code, Cursor, Increase, and Gemini CLI coding instruments throughout its developer base to help its core enterprise methods and develop its newer AI choices like customer-facing copilots and customizable AI brokers.
Devs use these instruments throughout a wide range of duties, the best of which embody information retrieval, code comprehension, good search, and code lookup. Egnyte’s code base has plenty of Java code, which makes use of quite a few libraries, every with completely different variations, Jassal defined. AI instruments are nice for peer-to-peer programming, serving to new customers get a lay of the land, or present customers probe into completely different code repositories.
“We have a pretty big code base, right?” Jassal stated. “Let's say you're looking at an iOS application, but you're not well versed; you will fire up Google CLI or an Augment, and ask it to discover the code base.”
Some Egnyte devs are transferring into computerized pull request summaries, which offer easy overviews of code adjustments that basically clarify the “what,” “how,” and “why” of proposed modifications.
“But obviously, any change that's made, we don't want to hear that AI made the change; it has to be that developer made the change,” Jassal identified. “I would not trust AI to commit to the production code base.”
Commits nonetheless go by human evaluate and safety validation, and something red-flagged is escalated to senior engineers. Devs are warned of the hazards of settling into autopilot mode or blindly trusting code. A mannequin could not have been uncovered to, or given sufficient samples of, sure coding parts and infrastructure in its coaching.
One other rising, and intently monitored, use case for AI is unit testing, the place code parts are run in isolation to make sure they work as meant. “At the end of the day, it is a productivity improvement tool,” he stated. “It is really a continuation, it's like any other tool, it's not some magic.”
Past core engineering, AI helps different groups collaborate with programmers. Product administration, as an illustration, is utilizing instruments like Vercel to deliver “demo-worthy” prototypes, fairly than simply concepts, to devs, who can then transfer forward with mock-ups. Or, if UX groups need to change sure components on a dashboard, AI can rapidly spin up a handful of choices, like completely different widgets or buttons.
“Then you come to engineering with that, and the engineer immediately knows what you really intend to do with it,” Jassal stated.
Setting expectations, assembly devs the place they’re
Nonetheless, day-to-day actions for all Egnyte engineers, together with junior builders, prolong past simply coding.
Junior builders are given hands-on duties throughout the total growth lifecycle to speed up their development and expertise, Jassal stated. For example, they help with requirement evaluation in early software program engineering phases, in addition to deployment, productization and post-deployment upkeep.
In flip, these actions require “Egnyte-specific tacit knowledge and experience” provided by senior engineers. One clear instance of labor that sits firmly with senior engineers is authoring structure notes, as these minimize throughout the platform and require a extra holistic, system-level view, Jassal stated.
“Many of the traditional roadblocks are navigated faster these days with AI; for example, understanding the codebase, dissecting requirements, auto-testing,” he stated. “This faster track allows our talented junior hires to progress more quickly and provide higher value to the company sooner.”
The corporate expects a a lot quicker studying curve from junior to mid-level engineers, Jassal stated. “It's always the case that people coming straight into the workforce are much more excited about trying new things,” Jassal stated. However that needs to be coloured with actuality to mood expectations, he added.
Alternatively, some senior engineers could have to be ramped up of their adoption as a result of they’re hesitant or had ho-hum or dangerous experiences with earlier era instruments. This requires incremental introduction.
“The senior people, having been burnt multiple times, bring that perspective,” he stated. "So both [types of engineers] play an important role.”
Hiring will continue for scale and fresh perspective
“In general, I would say it has been really hyped by folks who want to sell you tokens,” Jassal said referring to people who talk about human coders becoming obsolete.
"Vibe coding" could possibly be construed in the same vein: Like others in software program growth, he prefers the time period “AI assisted coding,” whereby programmers have a self-driven loop, producing code, analyzing exceptions, then correcting and scaling.
A minimum of in Egnyte’s case, hiring will proceed, even when at a slower clip as individuals change into extra productive because of AI, Jassal stated.
“We are not just hiring for scale, but to develop the next generation of senior developers and inject fresh perspectives into our development practices,” he stated.
The takeaway for technical decision-makers shouldn’t be that AI will remove engineering jobs — however that it’ll reshape how expertise is developed.
At Egnyte, AI-assisted coding is compressing studying curves and elevating expectations, not eradicating people from the method. Enterprises that deal with AI as a alternative danger hollowing out their future senior expertise pipeline; people who deal with it as infrastructure can transfer quicker with out shedding the judgment, creativity, and accountability that solely engineers present.
