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An AI engineer hasn’t touched code since December. He’s excited about AI, but worries about the future.

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This as-told-to essay is based on a conversation with Rohan Gore, a 38-year-old AI engineer at Reach3 Insights, a market research firm based in Vancouver. His identity and employment have been verified by Business Insider. The following has been edited for length and clarity.

I graduated with a computer science degree back in 2010, and I’ve worked in the industry since.

I started as a typical software engineer working on some of the interesting and complex problems in marketing research. Now, I’m an AI engineer.

I have mixed feelings about the impact of AI on the software engineering industry.

I completely handed off all my coding-related tasks to AI in December, and it did really well. I did not feel good about that initially. I’ve been coding for so long, and I realized at the time that coding is definitely gone.

I haven’t coded since then. That’s the new reality of my job. Just because AI has taken over my coding tasks, though, doesn’t mean I can play outside all day. I’m still able — and expected — to produce the same level of output and quality of work. Sometimes I feel burned out because the expectation is that I should be doing more work, even though AI can take over some tasks.

I’m excited about AI and enjoy how it’s changed my job

Right now, AI needs a lot of guardrails, and I believe that my background and systems knowledge still make me pretty useful.

I’m happy that I haven’t coded in three months because there’s a lot that I’m doing, like software architecture and design, that isn’t going anywhere. AI can help architect or design, but it needs a lot of hand-holding today. That makes the knowledge of software engineering more important than ever in the age of AI — at least for now.

There is also a lot of systems thinking that needs to be applied, which I love and am completely in harmony with, so it’s a good state for me.

I’ve been coding for years, and at the end of the day, it’s a means to an end. I never saw it as rocket science. But there is a lot of nuance to coding, which can be frustrating and tiring to work with at times. So, I’m enjoying this next era.

AI also lets me do a lot more research, and faster. It allows me to question product decisions and think more, rather than just execute. As an engineer, I was constantly under delivery pressure, but now it frees me up and actually allows me to critique what a project manager is doing, because I understand the product decisions that are being made. It helps me take on a broader product engineering role, which I’m enjoying.

I’m feeling happy that I can deliver at this pace, because that wasn’t possible earlier. It’s cool that I can make a feature in two or three days instead of a month. That’s a crazy transformation that I feel happy and excited about.

I’m concerned about the future

Even though I’m enjoying the current state, there’s always this behind-the-scenes thought of, “Ok, what’s next?” The technology is getting better every day. I’m not comfortable with AI being in a state where it can run on its own forever. I don’t know what I would do in that scenario.

It feels weird that the job has changed so much. Sometimes I find myself speechless. I have so many thoughts and emotions going on. Most of them have turned into excitement, but the more I think about it, the more it turns into fear. Sometimes I felt intimidated because these agents are so powerful.

I even openly said in my company’s Slack that there’s no way in my lifetime I could’ve coded something even 10% as good as these agents. At the end of the day, if you look at a typical problem, most humans are no match for solving them, unless you’re talking about the 1% geniuses.

Sometimes I feel defeated because coding was a skill I acquired over time and it took a lot of time to get to a state where I could do that well. It’s not that I don’t like the change, but there’s a fear there.

What happens if all of this gets completely automated and people just ask AI for things?




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Chong Ming Lee, Junior News Reporter at Business Insider's Singapore bureau.

I’m a senior software engineer laid off from Block. There are 3 things I’m keeping in mind as I reenter the job market.

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This as-told-to essay is based on a conversation with Isaac Casanova, who has worked at Block for nearly three years as a senior software engineer. It has been edited for length and clarity.

I wasn’t even looking at my computer at the time. One of my good friends started spam calling me. I picked up the phone, and he told me to check my email.

I read the email from Jack Dorsey, and I was like, whoa, I guess I don’t have a role anymore.

We were well aware that rolling layoffs were underway. Most people assumed it would be capped at 1,000. I didn’t feel like anything big like that was coming. For it all to happen at once like that is obviously a shock.

I never got a low rating. In my conversations with folks, I was doing fine. That’s why it’s characterized as a layoff, not a performance thing. This is just a change in business direction.

Check your ego — the industry is tough

I’m managing my expectations as I look for work.

It seems like companies are tighter with headcount and more picky about who they want.

There are definitely fewer positions. Companies are doing more with less. These agents are automating some tasks and are slowly improving at understanding concepts.

The compensation is definitely lower. We’re hearing across the industry that stock grants are lower than they used to be. Refresher grants are lower. Bonuses — if they exist.

Once you get in, it’s stack-ranked performance management. Your output is compared to your peers from day one. It’s definitely tougher.

You’ve got to check your ego. That might be the part people struggle with more than their technical ability.

Separate your identity from your job

At the end of the day, companies are beholden to shareholders.

Jack’s memo came across as what someone in that position making a tough decision would say. A call was made, and it had to be communicated. I don’t have any negative feelings about anybody that I worked with or at the company.

The biggest expense of running an organization is employees. The higher you are — senior engineer, engineering manager, head of product — the more expensive you are.

You need to remember that and evaluate your relationship with work. Many people in these positions tie their identity to their jobs. Those are the people most affected when these things happen.

You try not to take it personally. You see it as a new opportunity. There’s a human aspect — you just lost your job, and it kind of sucks for a bit — but you can’t let it hold you down. You can’t let it define you. These things happen, and you need to adjust.

The good thing about when these things happen is the network of people that you’ve met. Build the network so that when things like this happen, you can maneuver.

Be flexible — AI is changing the role

You could tell on the inside that things were changing.

A couple of years ago, I was doing most of the coding by hand. That slowly turned into using interfaces like Cursor, Claude Code, Goose, and ChatGPT. You’d slowly read things internally like, “Let’s speed up.” You were expected to speed up because the agents could make you more productive.

You’d have conversations with some of your colleagues and be like, “I haven’t opened my IDE in a month.” As a software engineer, that’s definitely a shift.

AI turns you from a person who just turns out code into more of an experimenter — a builder.

Software engineering, for a long time, was so by the letter, by the design, by the spec. Exact and precise, but slow.

Now we have these tools, the industry expects you to move fast. You can shift your mindset from that rigid engineering, step-by-step, to more of an exploratory “attack the problem, solve it, refine it later.”

Don’t get too trapped in the domain that you’re working in. Block tended to hire specialists who could also generalize when needed. So, be flexible. Using these tools allows you to get context in areas that you might not have had the opportunity to work in.

Do you have a story to share about tech layoffs? Contact this reporter at cmlee@businessinsider.com or on Signal at cmlee.81.




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Ex-Meta principal engineer shares 4 strategies to avoid being an underperformer

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Silicon Valley is raising its standards for talent.

Adrien Friggeri spent over a decade combined at Meta — including back when it was called Facebook — with stints at Michael Bloomberg’s Hawkfish and Clubhouse as well. Now, he works as a partner software engineer at Microsoft, according to his LinkedIn profile.

The consequences of underperforming are “more drastic” now than they were 10 years ago, Friggeri said on “The Peterman Pod.”

In an email to Business Insider, Friggeri wrote that there is less “organizational ‘slack'” and higher expectations for tech employees.

“That means performance gaps are identified and addressed faster, and if someone is not meeting clearly defined expectations over time, the path to a formal performance-management process (and potentially a role change or exit) can be shorter than it used to be,” Friggeri wrote.

Meta has been especially strict with its performance expectations. The tech giant laid off roughly 3,600 employees in February, labeling them low performers.

There are also benefits to being above the pack. Meta is introducing higher bonuses for top performers, Business Insider reported on Monday.

In his email, Friggeri clarified that the trend was not specific to Meta. Rather, it was industry-wide and reflected the state of the market. Meta did not respond to a request for comment.

Friggeri shared four tips with Business Insider to stay ahead and avoid underperformance.

1.) Workers should make expectations explicit.

“Align with your manager on priorities and what ‘great’ looks like for the next 30/60/90 days,” Friggeri wrote.

2.) Employees should seek out feedback.

They shouldn’t wait for review cycles, Friggeri wrote. Feedback should be sought out “early and often.”

3.) Focus on “visible, high-leverage work.”

“Pick projects tied to clear outcomes and communicate progress, risks, and tradeoffs,” he wrote.

4.) Keep investing in your skills

Friggeri wrote that employees should “treat learning as part of the job, especially as teams and priorities shift.”

On the podcast, Friggeri advocated for being independent and building new projects — and not being silent about them. It’s not helpful to “lock yourself in a room,” build for three months, and show up with the finished product.

“Overcommunicate is really the strategy I would recommend,” he said.




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Are you a software engineer? Tell us what you think about vibe coding

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  • Vibe coding has upended software engineering, strapping developers with a suite of new AI tools.
  • OpenAI and Tesla alum Andrej Karpathy, who coined the term, recently said he’s “never felt this much behind.”
  • Are you a software developer? Take our vibe-coding survey below.

Software engineering is changing — and we want to hear from those navigating the moment.

Programmers today find themselves with a whole new suite of AI tools, from Claude Code to Cursor to Codex. These editors enable engineers to generate entirely artificial lines of code or modify their handwritten code with the assistance of a large language model.

There’s a term for this type of AI-assisted programming: “vibe coding.”

Engineers from Meta to Google are embracing a vibe coding approach in their day-to-day work. Everyone, from teenagers to non-technical workers, suddenly seem to be building their own apps — or at least vibe-coding their way to a prototype.

It’s a whole new skill set for engineers to learn, though, one that can vary from tool to tool. (Replit is different from Lovable, which is different from Bolt, and the list goes on.) It’s also not clear, for the most experienced programmers, whether there are actually productivity gains.

Andrej Karpathy coined the famous term “vibe coding” early last year. He was a founding team member of OpenAI and led AI efforts at Tesla. In a recent X post reflecting on the field, Karpathy wrote that he had “never felt this much behind as a programmer.”

“I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year,” he wrote. “A failure to claim the boost feels decidedly like skill issue.”

Are you a programmer? Answer our vibe-coding survey below:




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Google engineer said landing an AI role took a year and daily studying

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This as-told-to essay is based on a conversation with Maitri Mangal, a 26-year-old software engineer at Google, based in New York. Her identity and employment have been verified by Business Insider. The following has been edited for length and clarity.

When I started off as a software engineer, my dad, who also works in tech, kept telling me to get into AI.

I brushed it off because I was just starting off my engineering career, and no one was really talking about AI in 2019, unless they were getting a PhD.

Then in 2023, the tech industry changed and everyone started going into AI. That led me to want to start pursuing AI as a job, and also creating content about it. When trying to join an AI team, I think having a strong presence and personal brand is crucial for others to take you seriously.

In my three years at Google, I’ve changed roles three times, most recently switching to the Workspace AI team.

It’s important to make a distinction between an AI machine learning engineer and an AI software engineer. An AI ML engineer creates the model, trains it, and evaluates it. An AI software engineer integrates AI capabilities into software applications, and builds APIs and infrastructure to serve the model to the end user.

My transition to an AI team didn’t happen overnight. It required spending about a year upskilling through courses and creating content about the material, which forced me to learn the concepts.

Here’s how I made the switch:

Creating content about AI

In the spring of 2024, I started creating tech content on Instagram and LinkedIn, outside my job. That became a major factor in my transition to an AI team.

Making content motivated me to keep learning and also made me confident about sharing what I knew. Once I started seeing how much it helped people, I wanted to learn more. So that’s where the upskilling started, and I started taking courses to understand the fundamentals of AI.

Eventually, I started applying to AI teams at Google. I felt like if I was going to spend so much time upskilling and making content about AI, I should make the most of what I had. I started searching for new roles in January, about seven months after I started upskilling. In March, I landed the new job.

I still spend an hour a day upskilling

I typically take Google’s internal courses to upskill. Coursera also has amazing courses.

The easiest way to start is by taking the basics of AI, like Google’s Introduction to Generative AI and Google Prompting Essentials. Since I have a computer science background, I was able to get more in-depth with concepts like linear regression and vector analysis.

I took courses for about two hours a day, but in order to absorb the material, I had to talk about it, not just read. When I verbalized the concepts through making content, it helped me understand the material.

I also get feedback from my followers, and when they ask follow-up questions in the comments, it makes me go even deeper into understanding a topic. Talking to friends or teammates who are excited about AI also helps me better understand the material.

In this field, it’s very hard not to learn. I’m not necessarily still dedicating two hours daily to courses, but I still spend about an hour a day upskilling, whether that’s in the form of internal trainings for my job, or watching YouTube courses for the content I create.

Not everyone wants to create content, so that’s not always the best way to go about transitioning to an AI team. If you’re just starting out in tech, my biggest piece of advice would be to take on projects. You should definitely take courses about AI, but keeping up-to-date with the news and doing AI projects also really helps. Many AI courses have users do mini projects, so you get to know how to work with it.

Since I applied internally, I didn’t have to go through the same interview process. However, I still had to submit my résumé, which included all of my side projects, and I think that really helps.




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