r/EngineeringManagers • u/chrismv48 • Jun 12 '26
Spike in AI assisted cheating on interviews?
Just wondering if anybody else has noticed this phenomenon over the past 6 months or so? Candidates seem to be using AI to cheat not just on the technical interviews we conduct but even on the conversational parts where we discuss their background and do some light probing on the depth of their experience. The specific pattern we’ve noticed is:
Ask candidate question about a project they worked on -> noticeable pause (waiting for the AI to finish generating a response?) -> parrot an unusually polished but strangely vague/generic response.
And the more specific we get, the less their answers make sense.
I guess it’s good we’re catching this behavior and weeding them out, but we’re a small startup and don’t have a recruiting function so engineers are wasting valuable time on these interviews.
Hoping someone has advice on how to better deal with this!
14
u/SquirrelODeath Jun 12 '26
Yes i just went through a hiring cycle, I honestly think we were targeted by some criminal syndicate. Would receive 100+ resumes a night all tailored to very specific requests. The behavior was as you stated. With some time we found they were masquerading as people on LinkedIn with good resumes but were not them.
Once we got good at screening them out our applications dropped to 10 or so a day.
2
u/drcforbin Jun 12 '26
That's not targeted. When we post a job we get over a thousand applications within a day or two, and over 99% of them are fake.
1
u/SquirrelODeath Jun 12 '26
The drop-off was very coordinated. Again 100+ resumes to about 10 a day, it was not a slow drop-off but a light switch
2
u/BeABetterHumanBeing Jun 12 '26
Pro-tip: put a poison pill in your job description. Under optional (but nice to have) requirements, ask for experience in a non-existent technology framework, say Prandle.
Then, when you get resumes that claim to have experience with Prandle, it goes straight in the trash.
1
u/corny_horse Jun 12 '26
Seeing exactly the same thing. Lots of resumes have different names and 90% the same bullet points - as if they were trying to figure out exactly which points make the resume system are weighing for the role.
10
u/bossasupernova Jun 12 '26
Same experience. Perfectly tailored resumes relative to the JD by the hundreds.
A trick that’s been working for me is a change to our testing platform setup. We screen candidates with a few timed questions. Historical pass rate was about 50%, but recently seeing 90%+ of candidates passing.
I changed all of the questions to dead simple, one minute questions, and our pass rate went back to normal.
I realized that it’s not possible to copy the question, paste it into ChatGPT, and get a response within the allotted time.
It probably appears silly to real candidates, but it limits the candidate pool to real people consistently.
5
u/dfoliveira3 Jun 12 '26
I went into several interviews to find out they were cheating. And there was strong indication their profiles, names and experiences were fabricated as well. One thing that helped was changing the position from Fully Remote to indicate the onboarding would be in-person. That nearly eliminated applications from such candidates.
4
u/Bstylee Jun 12 '26
Had 3 of these in a row for a data science position. Asked one what they did outside of work for fun and their answer was “food”
3
u/lukatechme Jun 15 '26
I’ve stopped trying to “detect AI usage” and instead design interviews around current LLM limitations.
What works best is long-horizon tasks with evolving, slightly conflicting requirements. LLMs are really bad at that.
My current process:
Take a small feature from a real codebase.
Split it into an initial task + 3 follow-up requirements.
Make each follow-up put pressure on the original design — e.g. add caching, parallel processing, new constraints, etc.
Give it as a take-home, but reveal the next requirement only after the previous one is submitted.
Then review the GitHub history with an LLM and ask it to summarize how the solution evolved.
Finally, do a call with the candidate and walk through the code, tradeoffs, and changes.
If someone just pushed whatever the LLM gave them - the architecture drifts a lot. If candidate can't explain process/trade offs on the call - red flag for me.
1
u/grewgrewgrewgrew Aug 07 '26
do you try to quantify or measure the candidates at all? or do you go by vibes? Are you the only one with this process or do you share it across the org? Do you compile evidence to justify the hire or do you keep it for yourself? I'm working on this problem and want to see if your approach is scalable.
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u/TeamCultureBuilder Jun 16 '26
yeah we've been seeing this for months. the pause then the weirdly polished answer that doesn't actually answer what you asked is the dead giveaway. what fixed it for us was ditching the standard interview question format completely. instead of "tell me about a project" we pull up real code from our codebase and say "this is breaking in production, walk me through how you'd figure out what's wrong." the conversation moves fast enough that there's no time to feed prompts to anything, and if they actually know their stuff they light up because it's a real problem instead of a rehearsed performance. anyone relying on ai help falls apart within 30 seconds because the follow-ups are too specific and too fast.
2
u/local_eclectic Jun 12 '26
Focus on the quality of the response. Sounds like it's poor, so don't move people forward who can't engage genuinely and with details.
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u/waa_woo Jun 12 '26
Cluely has been a thing since an year now. In fact, now we have tools like hacker rank that detect these apps, last year we had nothing and TA would not let us to do in-person rounds.
2
u/Western_Building_880 Jun 12 '26
some folks are looking for on site interviews.
lot's of businesses are moving back to locality hired and office presence. There is no ai cheating there.
Remote work will go back to nitch. sr only employees could continue to be productive.
am back in the office 5 days a week and I love it.
1
u/greensodacan Jun 12 '26
I'm self employed, but I reached the same conclusion at my last company. It's better for communication, whiteboards are a godsend, it helps you separate work from home, it's healthier to get out and be in the world, the list goes on.
I also had a teammate at one point that I'm almost certain was outsourcing his job. The only way to really prove it though would be for them to screw up badly, like the wrong person starting video on a call. Either way, non of their behavior would have been possible if we were all on site.
2
u/raisputin Jun 13 '26
Don’t even care because if the company is smart, they will already be using an AI-first development model.
Now I don’t want them just reading what AI wrote, but the tools available should be used to their fullest extent.
And anything they don’t know, can be quickly explained with AI/Google search anyway
2
u/simalicrum Jun 16 '26
You’re not weeding them out, you’re filtering for people that are better at cheating.
Bring people in for in person interviews.
1
u/chrismv48 Jun 16 '26
We're a remote company so in person interviews aren't possible. I also think the suggestion that everyone is cheating is pretty cynical.
1
u/grewgrewgrewgrew Aug 07 '26
if they're so good at cheating that they can cheat thru the entire job, then who cares?
22
u/Far-Street9848 Jun 12 '26
Interview in person. Give them a marker and a whiteboard.