Beyond the AI noise: How Stack Overflow is rethinking tech hiring

This post was originally published on this site.

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I’ve been recruiting into Stack Overflow’s product and engineering teams on and off since 2015, having originally joined the team when we were focused on our Careers product, and returning in 2021 to help build the teams that have built products like Overflow AI, Stack Internal, and more. Therefore, I feel quite uniquely placed to offer some perspective on just how much hiring has changed in the last 11 years, both as a talent professional and someone who’s spent most of their career doing that here at Stack Overflow.

The short and sweet take is that it’s gotten exponentially harder to identify talent that we feel is a good fit for our teams at the top of the application funnel. Part of that is down to there being proportionately more people actively looking for a new role at the moment due to the shift away from a candidate-led market to an employer-led one. Part of it is due to the emergence of new roles within machine learning and data science that didn’t exist ten years ago and lots of talented people moving into these exciting new roles. However, it would be remiss of me to not acknowledge that a big part of the problem is because, thanks to AI, bad actors and higher-than-ever distrust on both sides of the fence (employers and job seekers alike), the traditional resume just doesn’t give me trusted information into what qualifies someone to be a good fit for Stack Overflow anymore. It also means there’s more pressure to add more stages to what can already be long and convoluted hiring processes, just to be completely certain that someone can do what we need them to do—in the right place, at the right time, with the right intentions!

For example, we recently posted a job for a Staff Data Scientist on our careers page, and within 24 hours had received over a thousand applications. This is not a new phenomenon and has been de rigueur for us and many other companies over the last few years; however, what did stand out this time was just how similar some of the resumes were.

  • We received multiple applications that were formatted identically, with the same basic overview of the candidate’s experience, with very little to tell them apart from each other.
  • There were large numbers of resumes with links to social media profiles that didn’t exist, or that listed them as working in companies that didn’t exist at the time they purported to work there.
  • Despite putting a number of application questions in to glean more information from interested applicants, the popularity of tools like ChatGPT meant we received essay length responses that didn’t really answer the questions. Anyone can put those questions in an AI model and CTRL-V it over, but that makes it harder to tell if someone’s taken a shortcut or they’re not who they claim to be in the first place; plus, it makes everyone sound like the same person. It’s the ‘new Star Wars Trilogy’ problem: if everyone’s Han Solo, no one’s Han Solo.

We’re a small team on the talent acquisition side of the business at Stack. For one recruiter to look through this volume of either needlessly detailed or not-detailed-enough information makes it markedly harder to discern who we should invest time in at the start of the process to ensure we can find the right person quickly and effectively. It’s not news that talent teams are increasingly under-resourced across the industry, and yes, there’s definitely a reliance on AI at the sourcing stage to minimize the time it takes to find folks. But increased suspicion from candidates as to what happens to their resume once they hit ‘apply’ means that no one’s happy. Candidates feel under pressure to format their applications to bypass AI models that may or may not exist (depending on the company), and recruiters are becoming increasingly more suspicious as to the validity of who they might be speaking to once they decide to reach out. The system is broken, and as of yet, there’s no real solution.

That’s why, when the product team here decided to resurrect the Developer Story of yore, I was first in the queue to offer my input on how this could be something that would benefit everyone in the hiring process. I know what I’d love to see in a resume to help me make a decision on whether or not to schedule a first call with someone who reads like a fit. If we can take that instinct and combine it with nearly 20 years of experience helping technologists learn, help each other, and grow their careers, we could make a real difference.

Our vision for Developer Story is that it will be a way for anyone to showcase their work, their expertise, and their impact, be that in our community or in their career. Rather than guessing what employers are looking for, we want to leverage our experience and history to make sure you’re putting in the information that we know they want to see. On the other side of the fence, Developer Story is a way to focus in on the information that matters when trying to hire for a new position, giving recruiters more objectively verifiable insight into the person behind the resume and hiring managers a chance to see where the lines overlap between what someone has done, and what they’re going to do.

Even if you’re not looking for a job, Developer Story can be your place to collate and showcase everything you’ve worked on throughout your career and personal hobbies. That weekend app you built to time the perfect boiled egg? Put it in. That time you found the bug that was halting production at the last minute? That can go right alongside it. A full picture of your journey throughout technology, so that you can easily tell your story when the time comes to recount it.

Ultimately, Developer Story is a way to try and fix what’s broken within one part of the hiring process, as well as make sure that everyone gets a chance to stand out from the crowd and show the world what they’ve built, what they’ve learned, and what they’re going to do next.

Check out Developer Story today!

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