I'm a hiring manager on the product team at Coder, a growth-stage tech company founded in 2017. Everyone on the product team uses LLMs daily.
It's been fun to watch: docs folks fixing SEO issues on the website, engineers writing documentation, PMs building live prototypes, marketers shipping website changes directly. Nobody mandated any of this.
There are plenty of negatives too: layoffs, junior roles drying up, students worried about their careers, and a flood of low-quality generated content everywhere you look. I'm not going to solve those in this post. Instead, I'll share how AI actually affects hiring at one company that uses these tools heavily. If you're a candidate, I hope this helps you see how at least one company is thinking about it. I can assure you that we aren't alone.
Context on how we work
Every company values different things, so here's the environment my perspective comes from. If your values (or your company's) are different, your conclusions probably should be too.
We hire tinkerers. When I joined Coder, the first thing I did was stand up the product and poke at it. When I wrote my first blog post, I ended up also fixing the website's build process because it annoyed me. This attitude is company-wide. Nearly every department has built internal tools nobody asked for. We've also hired over 4 people directly from our user community, people who were already tinkering with the product before we ever paid them to. As we scale, we've had to get clearer about ownership, but I still want people who look outside their job description.
There's always more work than people. On the tactical side: improving our product's UX, writing a new feature or integration, improving documentation clarity, fixing a tiny bug. On the strategic side: better communication between departments, faster decisions.
We've seen a lot of hiring and firing. We're still a young company, but we've already been through plenty: we scaled too early once and paid for it with layoffs, and we've done hiring freezes while finding product/market fit. Right now we're hiring fast: 21 people in the last month, at a company of ~180. None of those layoffs or freezes had anything to do with AI. They came down to larger business reasons, the same boring ones that ended jobs long before LLMs existed.
What's actually changed
The number of open roles hasn't gone down. Expectations per role have gone up, but not in the way people assume. Myself and many of my peers are not concerned about squeezing more output out of everyone. It's about diversifying output in favor of impact: a docs person can contribute fixes directly, a PM can prototype their own ideas. This isn't about filling skill gaps. It's that going the extra mile got a lot cheaper, so we expect people to do it. We're less excited about "builders" in the raw sense, since building is cheaper than it's ever been. We're more excited about candidates who can demonstrate taste, understanding, and impact.
A good litmus test for me is whether someone is only using AI to generate new programs from scratch (likely to get scrapped/unmaintained), or to build on somebody else's ideas and understand a perspective or part of the company they haven't before. And then whether they actually get these shipped, improved, and retained. Getting 90% of the way there really doesn't matter
In practice:
- We filter for taste. I want to understand if the candidate has a perspective, an experience, or even a distaste for something, and whether they feel comfortable expressing and applying it.
- We still hire juniors (more than ever, actually). We just spun up a summer internship program, and we're hiring more junior roles than we ever have.
- Communication skills are more important than ever. If someone sends you sloppy AI-generated work, or you disagree with an idea, you need to be willing to say so. And when you don't understand something, loop in a colleague to collaborate, without dumping work on them to review or shipping while hiding your gaps.
My environment is not for everyone
Coder values tinkerers, fast-paced ownership, and people going the extra mile. We expect a lot out of people, and those expectations aren't always documented in some playbook. Not everyone wants to work in an environment like that, and that's OK.
I'm also only in one specific department of Coder (product management and developer relations), and other teams and roles will be different. AI will certainly automate tasks that are central to some jobs. I'm not saying everyone will be fine, that all employees will become curious, or that those who prefer to get a task, execute, and repeat will (or should) succeed in a knowledge worker economy. I'm also not saying we have all the answers or that Coder is AGI-proof; I just don't think those conversations are useful when it comes to hiring or getting a job. What I am observing is a significant positive impact on how we work together and how we build better products, and I'm optimistic about the companies we can build with it.
If you're looking to get into another industry or work environment, I'd push you to research what that company values and how they write about AI (I'm sure they are). If you're a hiring manager, it can be helpful to write about your experiences like I did today. If nothing else, it'll help candidates figure out where they're a good fit and what types of work environments excite them as AI changes how we work.
If you're a candidate
More than any specific advice, I'd encourage you to think about how hiring managers are thinking (this blog post reflects how I think), rather than treating posts like this as a checklist.
That said, a few things transfer anywhere. Joining the community of a product you want to work on (ours or anyone's) is a great way to learn it and see what people are actually working on.
Form real opinions about the things you use and build, and get comfortable sharing those opinions, including when you disagree with someone or how you can make something better.
At this point, it isn't even about showing or hiding AI usage in an interview. I'd recommend spending more time thinking about how you can apply your unique skills to make the company better than showing off what you've built, unless what you've built has users and impact.
And if you're earlier in your career, don't count yourself out. As I mentioned, we're hiring more junior roles than ever, and I know we're not the only ones.
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