u/SatisfactionSevere46

was venting to her about my job search going nowhere and she just looked at me and said "how do you think they're reading your resume?" and honestly I had no idea. she's been on hiring panels before so she broke it down for me.

apparently recruiters go through three stages. first they skim to check if you're even remotely qualified, we're talking a few seconds. then they scan for keywords that match the job description. only if both of those pass do they actually sit down and read the whole thing. I had been writing my resume like someone was carefully reading every word top to bottom and that's just not what's happening.

the thing that really got me was when she said a former colleague once filtered out half the applicants for a role just because a specific skill wasn't written on the resume. didn't matter if the person actually had it. if it wasn't there he moved on because he didn't have time to find out. I redid my resume that same night honestly. what's one thing about how hiring actually works that you wish someone had told you earlier?

the tech roles holding up right now share one thing. they require judgment in situations AI has never seen before, accountability for real outcomes, or human context that can't be prompted into existence. cybersecurity is the clearest example since attackers adapt constantly with methods that didn't exist last month and you can't automate the intuition of someone who thinks like a threat actor. software architects and senior engineers aren't going anywhere either because AI can generate code but cannot decide whether your architecture will scale, whether the trade-offs you're making now become technical debt in two years, or whether what you're building actually solves the business problem. product managers sit in rooms with clients who don't fully know what they want and extract actual requirements from what gets said. that combination of judgment and human reading of a room is not promptable. AI and ML engineering is the fastest growing category with postings up nearly 60% from 2020 levels because someone has to build, audit, and improve these systems.

the salary data makes this concrete. workers with AI adjacent skills are earning more than peers in identical roles without them. AI integration specialists and trainers are pulling between $95,000 and $200,000. the highest paid aren't pure technologists, they're people who combine AI fluency with deep domain knowledge and the judgment AI keeps failing at. the pattern is consistent across all of these roles. if a job is predictable and rule based AI automates it. if it requires reading a situation that has never happened exactly this way before, the human stays.

Talked to someone who used to manage and train recruiters and the thing that stuck with me is how often qualified people get rejected simply because the recruiter reading their resume doesn't understand the industry at all. Someone in finance gets compared against a recruiter who's never worked in finance. Someone in IT gets screened by someone who's never touched the technology being described. If the resume doesn't translate clearly enough, the recruiter doesn't ask questions, they just decline, because admitting they didn't understand it looks worse to them than rejecting a good candidate.

That changes how a resume needs to be written. It's not about impressing someone in your field, it's about being understood by someone outside of it. If you're in sales that means leading with revenue increases and awards because that's the proof a non-sales recruiter can recognize. If you're in finance it means showing how you saved the company money in plain terms instead of technical detail. If you're in IT it means explaining what a tool actually did for the business instead of assuming the acronym speaks for itself.

The keywords and buzzwords recruiters search for aren't filler, they're often the only bridge between what you actually did and whether a non-expert screening your resume can recognize that it mattered.

It's not that the system is testing your competence accurately. It's testing whether a stranger with no background in your field can understand your value in about six seconds.