If you’re over 40 and looking for work right now, the math has been confusing. You have decades of relevant experience. The job description reads like your résumé. You hit “Apply” — and within a few hours, sometimes minutes, the email lands: “We’ve decided to move forward with other candidates.” No interview. No human ever saw the file.
Then the April 2026 Mobley v. Workday lawsuit news crossed your feed and a lot of working-age dread suddenly had a name. The lawsuit is a class action; the class definition is “applicants 40 and over rejected by Workday-deployed AI screening since 2020.” On r/recruitinghell, u/Orome2 (5+ upvotes, April 2026) posted what felt like everyone’s first reaction:
“Over 40 per the lawsuit. Makes sense why I get instant rejections to jobs posted on company websites that use workday. Job postings that are right up my ally or I’m even overqualified for. Just turned 40 this year.”
You are not crazy. The screening is real. And — useful detail — you can run the same kind of AI screening on your own resume before submitting it, see the exact score, see the flags, and rewrite to bypass the filter.
This post is the candidate-side version of the lawsuit. The ChatGPT prompt that simulates how an ATS reads your resume, the age-flag hack the prompt surfaces, and the rewrite tactics over-40 candidates have been quietly sharing on Reddit since the lawsuit hit.
The Problem in One Paragraph
Modern ATS (Applicant Tracking System) software uses AI scoring to filter candidates before any human sees the resume. The filters are trained on past hires — which, statistically, skew younger. The AI learns “younger-shaped” résumé features (recent graduation years, less experience, certain phrasing patterns) and treats them as positive signals; it learns the opposite signals as negative. The over-40 résumé walks into the filter with a structural penalty before the content gets read. The Workday lawsuit is the first major legal challenge to this. It will not move fast enough to fix the next 100 jobs you apply to. The candidate-side fix is to know what the AI sees, and rewrite accordingly.
The pain is universal in the public-thread record. From @middle_class_us on April 9, 2026 (345 likes, 79 reposts, 4.1K views):
“You did everything right. Went to school. Built a career. Stayed loyal. Worked 20+ years. Now you’re over 40 and suddenly ’not a fit.’ That’s a system dumping its most expensive people. AI is cheaper. Younger workers are desperate for a job. So you get tossed aside.”
From u/AcesAnd08s on r/recruitinghell (33 upvotes, April 2026):
“I’m 54 now and still feel young, smart, and fully capable. But I can’t even get anyone to look at me. I have a stellar resume, loads of relevant experience, leadership positions at major firms, etc.”
If those quotes feel painfully familiar, the rest of this post is the practical part.
The ChatGPT Prompt: Run Your Resume Through a Simulated ATS
This is the prompt that’s been circulating on Reddit (most prominently in r/ChatGPTPromptGenius and cross-posted to r/jobs and r/recruitinghell during April 2026). I’ve cleaned it up and added the age-flag specifics that the original wasn’t surfacing.
How to use it: Open ChatGPT (or Claude, or Gemini — works in any of them). Paste the prompt below. Replace {PASTE YOUR RESUME} with your actual resume text. Replace {PASTE THE JOB DESCRIPTION} with the actual job ad you’re applying to. Run it.
You are a strict Applicant Tracking System (ATS) AND a senior recruiter
with 20+ years of experience screening candidates at scale.
Read the job description below, then read the resume.
Score the resume the way an automated ATS would, focusing on:
1. KEYWORD MATCH (0-100): How many of the job's required hard skills,
tools, certifications, and exact-phrase requirements appear verbatim
in the resume.
2. EXPERIENCE-LEVEL FIT (0-100): Whether the resume's seniority signal
(years of experience, scope, titles) matches what the job is asking for.
3. AI-AGE-SIGNAL FLAGS: Identify any features that an automated screener
may use as proxies for candidate age, including:
- Graduation years older than 15 years ago
- Job experience descriptions that span more than 20 years
- Use of dated technologies, certifications, or terminology
- Date formatting patterns that reveal long career history
- Any phrasing that signals "veteran," "longtime," or seniority in
a way that may filter out under blind ATS rules
List each flag with the exact line/word from the resume.
4. MISSING HARD SKILLS: List the skills the job requires that don't
appear in the resume (verbatim or synonyms).
5. REWRITE RECOMMENDATIONS: Specific edits — sentence by sentence —
that would raise the keyword match and reduce the age-signal flags
without changing the truthful content of the resume.
Output as a structured report:
- Match Score: X/100
- Experience Fit: X/100
- Age-Signal Flags Detected (list with exact resume line)
- Missing Hard Skills (list)
- Top 5 Rewrite Recommendations (specific lines + replacement text)
- Final Verdict: Pass / Borderline / Likely Filtered
Be brutally honest. I am the candidate; I want to know what the ATS sees,
not what's polite.
JOB DESCRIPTION:
{PASTE THE JOB DESCRIPTION}
RESUME:
{PASTE YOUR RESUME}
How to copy: Click in the code block, press Cmd+A (Mac) or Ctrl+A (Windows), then Cmd+C / Ctrl+C to copy.
What you’ll see: Within 20-30 seconds, ChatGPT will return a structured report with a numeric match score (typically 30-85 for over-40 candidates on first pass), a list of age-signal flags with the exact lines that triggered them, and 5 specific rewrite recommendations. The brutal-honesty framing matters — without it, the model softens the diagnosis.
What to do with the output: Take the rewrite recommendations seriously. They’re not telling you to lie. They’re telling you that the exact phrasing of “20+ years of progressive leadership” reads to an ATS as a seniority-and-cost signal that filters you out, while “led teams of up to 40 across three continents” is the same truth without the age tell. Rewrite. Re-run the prompt. Watch the score climb.
If it doesn’t look right: If ChatGPT asks clarifying questions like “What industry?” or “What seniority level?”, give it the answer in one line and ask it to proceed. If the output is too short or vague, add to the bottom of the prompt: “Output at least 800 words. Be specific. Quote the exact resume lines you’re flagging.”
What the Prompt Actually Catches
The age-signal flags are the part most candidates don’t know to look for. Here’s the pattern from candidates who’ve run the prompt and shared screenshots on Reddit:
Graduation years
The single biggest flag. From u/Ok-Faithlessness1671 on r/resumes, April 2026, in a thread on the same topic: “Yes, leave your graduation year out always.” And from u/[deleted] in the same thread (7 upvotes): “Yes, you should. Ageism is a thing. It doesn’t help to have dates.”
The ATS scoring algorithm treats a graduation year of 1995 as a near-deterministic signal that the candidate is over 50. The fix is not to lie — it’s to omit the year entirely. Most ATS systems do not penalize the absence of a graduation year; they only penalize the presence of an older year. List the degree, list the institution, omit the year. The recruiter who actually interviews you can ask if it matters; the algorithm cannot.
Experience description length
A “Senior Director, 1998–present” line tells the algorithm: this person has 28 years of experience, which correlates with high cost and (statistically, in the training data) lower hireability for the role. The fix is to compress: list the most relevant 10-15 years explicitly, then a “Earlier career” one-line summary covering everything before that. You’re not hiding the experience — it’s all available on LinkedIn, in the interview, in references — you’re not feeding the filter the structured data point that triggers the penalty.
Dated technology references
“Proficient in Lotus Notes” or “managed Novell network” reads to the AI as evidence of pre-2005 work. Even if you’re now at a senior level on modern stacks, the ATS will weight the older signal heavily. Move dated tech to a “Selected technical history” line at the bottom; lead with the modern stack you actually use.
Phrasing that signals seniority cost
“20+ years of progressive leadership” is honest. It is also the line the ATS will rate negatively because the system has been trained that “20+ years” candidates are more expensive than “10+ years” candidates with similar role titles. “Led the engineering function from 8 to 80 engineers” is the same truth without the year-count tell.
The Reddit thread from u/Three3Jane (r/recruitinghell, 13 upvotes) caught the systemic frustration: “Yes the whole BuT yOu’Re gOInG tO rEtIRe sOoN, RiGhT? attitude because you’re on the wrong side of 50. Buddy, I’m 54 and I’m lucky if I’ll get to retire when I’m 72 - if at all.” The candidate is not the problem. The training data is. The fix is to give the ATS less of what triggers the cost-association.
The Workflow That’s Actually Working
From the patterns in the April 2026 threads, here’s the realistic candidate workflow:
- Run the ChatGPT prompt above on your current resume + a target job description. Note the score, note the flags. This is the baseline.
- Apply the rewrite recommendations. Don’t lie. Just remove the age-tells the prompt surfaced. Re-run. Score should climb 15-30 points.
- Maintain two resume versions. A “human network” version (full career history, exact dates, the works — for LinkedIn and for warm intros) and an “ATS submission” version (filtered as above). These are different deployment targets, like different builds of the same code.
- Avoid Workday-system applications when there’s a non-Workday alternative. Many companies post the same job on multiple boards — LinkedIn, Indeed, the company’s own ATS, sometimes a recruiter inbox. The lawsuit class is specifically Workday-screened applications. Other ATS vendors have their own biases, but the Workday biases are the ones currently under federal certification. Where you have a choice, route through the path that doesn’t sit inside the litigation.
- Save the audit reports. Every time you run the prompt against a real job description, save the output. Patterns emerge across 20+ runs — particular industries, particular companies, particular titles consistently flagging your resume harder. That data informs where to spend your application energy.
The candidates running this workflow are reporting score improvements and, more importantly, interview rates that look more like 2018 than 2024. From u/DuncanEllis1977 in the lawsuit thread (the comment chain that drew ~277 upvotes): “It explains why I was getting insta-rejections from things I was 100% qualified for when I was laid off a year and a half ago.” Once the explanation lands, the workflow follows quickly.
What This Won’t Fix
A few honest disclaimers, because the prompt is a tool, not a magic wand:
- It won’t fix systemic bias in the hiring funnel. It will help you get past the first AI gate. The rest of the funnel — recruiter calls, hiring manager screens, panel interviews — has its own bias surfaces that this prompt doesn’t address.
- It won’t help if the underlying job is mis-targeted. Running the prompt against a job that’s genuinely a stretch will return a low score for legitimate reasons. The prompt distinguishes between “the ATS is unfairly filtering this” and “the resume is genuinely not a fit,” but you have to be honest with yourself about which is which.
- It is not legal advice for the lawsuit. Mobley v. Workday is real, the class certification is real, and the opt-in window matters if you’re in the affected category. Read the law firm pages directly. This blog post is not your legal counsel.
- The prompt evolves. ATS systems update. AI scoring changes. The version of the prompt above will hold for most 2026 ATS systems but will need refresh as vendors react.
What to Do This Saturday Morning
If you’re 40+ and currently job-hunting:
- Open ChatGPT (or Claude, or Gemini) and paste the prompt above with your most recent resume + a job description you’re considering applying to. Take 15 minutes. Read the output.
- If the score is below 70 and there are age-signal flags, do the rewrite recommendations first, then submit.
- Save the prompt. Run it on every application going forward. The 90 seconds it costs you per application is worth orders of magnitude less than another six months of “we’ve moved forward with other candidates” emails.
- Forward this post to one other person over 40 who’s job-hunting. They probably haven’t seen the prompt.
For HR managers reading from the other side: this is what your candidates are doing now. The ones who know the prompt will get past your filter; the ones who don’t, won’t. If your goal is to hire the best candidate rather than the youngest-looking resume, the AI for HR (Legal-Safe) course walks through the audit framework that brings your filter into compliance with ADEA and the post-Mobley standard.
The lawsuit is necessary. The lawsuit is also slow. While it works through the courts, the candidate-side fix is in your hands. Twelve minutes, one prompt, one rewrite. The interview you missed last month wasn’t because you weren’t qualified. It was because the algorithm decided before any human could. Now you have the tool to argue back.
