For eight years, an Indian-origin software engineer, Akaash Vishal Hazarika based in Seattle has had a rare front-row seat to the changing world of Big Tech. Having worked at Google, Amazon, Splunk, and now Salesforce, they have watched software engineering transform in ways that many aspiring engineers still don’t fully understand.
What has changed most is not just what engineers build, but how they are expected to build it and how quickly. In a personal essay he wrote for Business Insider, he explains three realities of engineering world today.
Reality 1: Coding alone is no longer enough
The engineer says the biggest shift is the role of artificial intelligence in everyday work. AI is no longer a “nice to have.” It is now assumed. “I personally make heavy use of AI to help me with boilerplate stuff so that I can concentrate on the hard stuff, like system design and complex business logic,” he told Business Insider.
AI does the repetitive work, and engineers are expected to use the saved time to solve tougher problems. Because of this, companies now expect engineers to be faster, sharper, and more reliable than before.
Preparing to be a software engineer today is very different from five years ago. “When I was interviewing for software engineering jobs in 2020, LeetCode and system design were the de facto standards for cracking a job interview. Job seekers who had an advanced understanding of data structures and algorithms would come out on top,” he told Business Insider.
That knowledge still matters, but it is now only the starting line. “Today, this is just the baseline expectation,” he explained to Business Insider. Engineers are now expected to know how to work with AI and not compete against it.
Reality 2: Interviews are testing something new
Many candidates still prepare for interviews as if it is 2020. But interviews themselves have changed. “Interviews have also evolved with the arrival of AI,” he explained to business Insider.
You still need strong fundamentals such as problem-solving, system design, and debugging skills. In fact, debugging has become even more important because AI tools can make basic logic mistakes. But something surprising is now happening in interviews.
“I’ve seen firsthand that working with AI assistants in live screen-sharing mode is now allowed in some interviews,” he told Business Insider.
In one interview with a Silicon Valley startup, the engineer expected a normal coding test. Instead, they were given a large, messy code file and asked to fix a bug. The interviewers clearly said AI tools were allowed. “I ignored the invitation to use AI, thinking I was supposed to do it myself, and ended up spending a lot of time on the problem to no avail. I failed that interview. That was an eye-opener for me about AI’s new role in this field,” he explained to Business Insider.
Companies are not testing whether you can avoid AI. They are testing whether you know how to use it wisely to reach a business goal. Some interviews now even ask candidates to explain where AI fits into a system and where it doesn’t.
“You may also be asked system design questions about where AI should be integrated into the current business workflow, or to discuss the trade-offs of using AI and traditional approaches in various problem contexts,” he stated.
Reality 3: Engineers are expected to think like product builders
Today’s software engineers are expected to think beyond writing code. They must understand cost, scale, reliability, and real-world impact. The engineer noticed that companies are giving candidates access to small codebases and asking them to deliver working features in about an hour.
“What I’ve seen is that companies give access to a small codebase and expect you to deliver a small feature in about one hour, which is impossible without AI. With AI, you can roll it out easily,” he told Business Insider.
Behavioural questions have also changed. Instead of only asking about teamwork or conflict, interviewers now ask questions like how you decide when to use AI and how much human control should remain.
Senior engineers, in particular, are expected to build what the techie calls an “AI product mindset” which means thinking carefully about whether to use third-party tools, open-source models, or traditional systems, and understanding the trade-offs between cost, speed, and reliability.
What this means for new and experienced engineers?
For fresh graduates, they have to show that you can work on real systems, not just solve textbook problems. Being able to explain why you made certain decisions matters as much as making them.
For experienced engineers, deep knowledge is still your biggest strength, but it must be paired with AI skills. The goal is not to become a “prompt-only” engineer, but someone who understands both engineering fundamentals and AI-powered workflows.
“If I were interviewing, I’d position myself as a ‘hybrid engineer.’ Don’t just be a pure coder or just a prompt engineer. Be the bridge,” he added.