This essay is based on a conversation with Manoj Aggarwal, a senior software engineer at a large software company who previously worked at Microsoft, Twitter and Stripe. He is in his 30s and lives in California. The following has been edited for length and clarity.
I worked as a software engineer for 14 years at companies like Microsoft, Twitter and Stripe – and I’ve seen the job change.
I think in some ways it’s a fun time to be a software developer. There are so many tools available that you can create virtually anything from scratch without your own skills being the bottleneck.
It is also a challenging time for many engineers. AI tools have made coding easier, but ultimately engineers – not AI – are responsible for the code that gets shipped. Even though AI speeds up and makes many parts of the code review process more targeted, the added responsibility of reviewing AI-generated code can contribute to burnout.
There are also concerns that AI could replace engineers. While two years ago it took ten engineers to deliver a project, today it may only take five.
I think young engineers might be the most affected. When I was job hunting last year, there seemed to be more openings for senior engineering positions than for junior positions, and I think companies will continue to rely on experienced engineers working with AI tools.
That’s one of the reasons I make sure I stay current with these tools.
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I stay up to date with the AI even after work – without compromising on my work-life balance
My current job is a technical position at a large software company, and AI has completely changed my workflow in the last year. My programming time has essentially been reduced to writing prompts for AI tools, and in some cases I’m working at a pace that feels like ten times faster.
I learn a lot about AI at work. Still, I think it’s important to spend a few hours a week outside of work experimenting with AI to stay up to date on the industry. This also allows me to work on cool projects that wouldn’t be possible during work hours because my day is so full of office work.
The time to experiment with AI outside of work didn’t have a big impact on my work-life balance. A big reason for this is that I have a toddler at home, so I can’t even think about opening my laptop while he’s awake. When I work on personal projects or read about AI, it’s usually at night after she goes to sleep or on weekends – when she’s sleeping.
I spend less than $100 per month on AI tools and created my own chatbot
Outside of work, I often use Claude Code, Microsoft Copilot and Lovable. I spend around $50 to $60 per month on Claude Code, depending on how many tokens I use and the subscription price. I recently tried Anthropic’s Fable model for a personal project and wow, it’s fast.
One of the side projects I created is an open source tax and finance assistant. This allows users to connect AI models such as Gemini or ChatGPT and upload financial documents such as credit card statements, investment portfolios and tax forms. The tool can analyze these documents and point out things like overspending in certain categories, expensive subscriptions, or whether an investment portfolio may be too aggressive or too conservative.
I used the tool to prepare my 2025 tax return and it helped me verify that my CPA did everything correctly. I built it to run locally on my computer because I didn’t want to upload my personal financial information to AI models over the internet.
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Engineers should rely on the domain knowledge that AI does not have
One of the biggest challenges engineers face is adapting to a job that can change quickly due to technological changes and other factors beyond your control. This was already true before the AI boom.
In recent years, generative AI has raised new questions about job security for engineers. It’s important to keep up with AI, but I also think that AI doesn’t have the general picture of what a system should look like or why it’s designed a certain way. This is where I think engineers still add value. I would suggest leaning on your experience – both your technical skills and the institutional knowledge you’ve gained from being at a company for a while.
Although some projects may require fewer engineers in the future, I think the responsibility of the remaining engineers will be very important. AI also makes mistakes, so a human needs to be in the loop.
My advice to other engineers would be to not shy away from keeping up with AI. No matter how you feel about AI, if you are compared to another engineer using it, there is no doubt that the other engineer’s productivity will be higher. So experiment with different AI tools and find what works best for you.
Do you have a story to share about learning AI or working in tech? Contact the reporter by email at jzinkula@businessinsider.comor via Signal at jzinkula.29.
https://www.businessinsider.com/software-engineer-ai-tools-could-reduce-junior-engineering-tech-jobs-2026-7
