A Bay Area-based Google engineer has opened up about the impact of AI on the tech landscape. Harsh Varshney, a machine learning software engineer at Google, spoke to Business Insider about the transformative role of artificial intelligence in how companies are building, hiring and rethinking their future.
Varshney holds bachelor’s degree in electrical engineering from BITS Pilani and a master’s in computer science from Carnegie Mellon University. He joined Google two years ago after stints at Flipkart, Amazon Web Services, Splunk and other companies.
The changing world of Big Tech
“The world of Big Tech has become much more dynamic and results-oriented than the one I entered just a couple of years ago,” he wrote for Business Insider.
Traditionally, software development relied on long planning phases and multi-week sprints. Today, this approach has been streamlined for agility and faster execution, says Varshney.
The Indian-American techie says there are now more opportunities for software engineers to create “impact”.
AI becomes indispensable
Varshney says that the rise of generative AI has been the biggest shift. Back in 2017, when he started his tech career, AI was a niche field. Today, it’s a core skill built into almost everything, completely transforming the role of a software engineer.
{{/usCountry}}Varshney says that the rise of generative AI has been the biggest shift. Back in 2017, when he started his tech career, AI was a niche field. Today, it’s a core skill built into almost everything, completely transforming the role of a software engineer.
{{/usCountry}}“You're no longer just building an application; you're expected to build the intelligent systems that power it,” he wrote, noting how demand for experts in machine learning as well as emerging technologies like agentic AI has skyrocketed.
From days to hours
The Indian-origin techie says that AI has also had a huge impact on his job. Tasks that once took days can now be completed in hours.
“AI tools now shape how I debug, experiment, and optimize, turning workflows that once took days into hours. The expectation is clear: It's not enough to build something that works — it has to be smart,” he wrote.
“The rules of data have fundamentally changed.”