Same.

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.

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.

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nerdsniper 2 hours ago | parent | next [-]

I wish it was at least normalized to submit two resumes - one for AI and one for humans. Threading the needle to please both audiences is such a crap-shoot.

	▲	8note 31 minutes ago \| parent [-]
		im kinda thinking about adding an llm resume to my resume as like tiny clear text somewhere in the corner.

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jwolfe 2 hours ago | parent | prev [-]

> 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.

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.

	▲	majormajor 4 minutes ago \| parent \| next [-]
		A couple issues I have with this in particular: > "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.
	▲	dolebirchwood 2 hours ago \| parent \| prev [-]
		Because the latter's "business impact" is clearly made-up bull shit?