FWIW, when I see a resume with metrics and keywords, I immediately filter it out.
FWIW, when I see a resume with metrics and keywords, I immediately filter it out.
If it's something like "Refactored the apartment list service improving P99 Latency from 2s to 180ms", it definitely boosts the resumé in my mind. A good engineer would be measuring their impact and likely have numbers like that off the top of their head.
But if it's like "Increased revenue by $18.7M by reducing time-to-first-interaction latency from 2.3s to 117ms, increasing conversion by 47% and LTV by 28%," with the same fidelity on each bullet, I'm very skeptical.
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I don't summarily reject AI-written resumés to be clear, as honestly, it's basically a necessity at this point to be competitive with others; it'd be putting yourself at a severe disadvantage on pure principles in a way that has no real positive net effect on society. Even if you disagree with AI resumé screeners, you're only hurting yourself — especially at a time that has the largest impact on your compensation (i.e. negotiating salary at job start is one of the most valuable ways to spend your time since it will pay you back every paycheck).
Though I _do_ tend to question resumés that look like they were written almost entirely by an LLM without the candidate providing significant context and refinement.
> But if it's like "Increased revenue by $18.7M by reducing time-to-first-interaction latency from 2.3s to 117ms, increasing conversion by 47% and LTV by 28%," with the same fidelity on each bullet, I'm very skeptical.
Do you mind explaining why? The former doesn't indicate caring about business impact whatsoever (is this service in the critical path of any online process? Who knows!) while the latter does.
> "Increased revenue by $18.7M by reducing time-to-first-interaction latency from 2.3s to 117ms, increasing conversion by 47% and LTV by 28%,"
The first is that they're playing fast and loose with their numbers. Latency has before/after, conversion and LTV have percentages; revenue is just a single number. Did that double revenue? Or is that half a percent, and is it lost in the statistical noise?
The other is that there's nothing there to convince me that the technical work was was the full cause, instead of, say a new marketing promotion that launched at the same time, or another team redesigning the landing page flow, or another team re-doing all the product photography, or any other concurrent work.
Maybe all those questions have good answers, but I would at least want some nod in there to how they validated it. I find people who focus on "business impact" but don't know how to do the math to have confidence in it dangerous, because it's so easy to cherry-pick numbers that will make execs happy at a glance and prioritize for those things instead of actual long-term system or product or customer-facing improvements.
I'm not binning the resume for it, and maybe it helps get past the people who see it before I do, but I'm gonna dig in on it. And I'm usually disappointed by the answers.
This used to be called "buzzword bingo" and was pretty much required. It was how you got past the initial automated filtering step before a human even saw your resume.
For my own resumé, I include the stack used at each job which I feel strikes a fair balance.
Most applicants have no idea about your internal HR procedures and what's the pipeline before the resume even gets from you so they might as well optimize for what generally seems the most "successful" approach. Maybe they actually think writing metrics and keywords is a good idea, maybe they think its stupid and resent it but can't get any interviews without it, its really impossible to tell without other variables..
what i am researching right now is if you (hiring manager) got 2 resumes from the same candidate, one hand-written (metaphorically) and the other built by chat-GPT or AI, which one would you call ?
I would not can it in isolation, but if I see a comma-separated list like: “proficient in redux, react, html, JavaScript, sql, kubernetes, word and excel”… then yes, you don’t make the cut.
Or if you list your Microsoft qualifications or your MIT continuing education courses. These are all negative signals.