{"title":"How AI Screens Resumes","description":null,"content":"AI is now part of many hiring workflows, but it is not always doing what candidates imagine. In some companies, AI tools summarize resumes. In others, they help recruiters search, sort, or compare resumes with job descriptions. Some companies use very little AI at all.\n\nThe safest approach is not to write for a machine. Write a resume that is clear, specific, truthful, and easy for a recruiter or hiring manager to understand. That same resume is also easier for software to handle.\n\n---\n\n# How AI Screening Works\n\nAI-assisted screening adds a layer on top of the usual recruiting workflow. Instead of only matching exact keywords, some tools try to understand whether your experience is related to the role.\n\nFor example, a keyword search may look for the exact word \"Kafka\". An AI-assisted tool may also connect related phrases such as \"event streaming\", \"message queues\", or \"Kafka-based pipelines\". That can help when your resume and the job posting use slightly different wording.\n\nBut AI does not fix a vague resume. If your resume is hard to follow, uses inflated language, or hides the most relevant details, the tool may produce a weak summary. A recruiter or hiring manager may have the same problem.\n\nAI tools usually show up in a few practical ways:\n\n- **Matching.** Comparing a resume with a job description to estimate how closely they fit.\n- **Summaries.** Creating a short candidate summary for a recruiter.\n- **Search support.** Helping recruiters find candidates whose profiles look related to a role.\n- **Sorting.** Helping recruiters organize a large applicant pool.\n\nNot every company uses all of these. Many still rely heavily on recruiters, ATS filters, knockout questions, referrals, and hiring manager review. The exact workflow varies by company, role, and market.\n\nThat is why the best resume strategy stays simple: write plainly about real work, use the job's language when it is true, and make your strongest evidence easy to find.\n\nGood AI tools and good human reviewers both need the same raw material: what you worked on, what tools you used, how much ownership you had, and what changed because of your work.\n\n---\n\n# Using AI as an Assistant\n\nUse AI as an assistant, not as the author of your resume. It can help you compare, organize, and sharpen. It should not invent your story or replace your judgment.\n\n### Start with the job description\n\nPaste the job description into an AI tool and ask for a plain list of required and preferred skills. Keep the instruction narrow:\n\n\n```javascript\nRead this job description and list the required skills and preferred skills.\nUse only terms that appear in the posting. Do not add skills that are not\nmentioned.\n\n[paste job description]\n```\n\n\nThis gives you a checklist. It also reduces the chance that the tool adds skills that sound likely but are not actually in the posting.\n\n### Compare the list with your real experience\n\nRead the list yourself. Mark each item in one of three ways:\n\n- I have this experience, and it is already clear on my resume.\n- I have this experience, but it is missing or hard to find.\n- I do not have this experience.\n\nThe diagram below shows how each of the three marks leads to a different action.\n\n\n```mermaid\nflowchart TD\n A[Required skill
from the posting]:::start --> B[Have it and
already clear]:::stage\n A --> C[Have it but
buried or missing]:::stage\n A --> D[Do not
have it]:::stage\n B --> E[Leave as is]:::keep\n C --> F[Edit: surface it
where the work was]:::edit\n D --> G[Real gap,
do not fake it]:::gap\n\n classDef start fill:#00ceff,stroke:#000,color:#000\n classDef stage fill:#ffd43b,stroke:#000,color:#000\n classDef keep fill:#69db7c,stroke:#000,color:#000\n classDef edit fill:#ffa94d,stroke:#000,color:#000\n classDef gap fill:#ff8787,stroke:#000,color:#000\n```\n\n\nOnly the middle branch is resume editing work. The first needs nothing, and the third is a real gap. Do not try to cover it with vague wording. If a role requires Kubernetes and you have never used it, no AI rewrite should make it sound like you have.\n\n### Add missing skills only where they belong\n\nIf you have a skill but it is not visible, add it where the work actually happened.\n\nFor example, if you used PostgreSQL on a project but wrote only \"built database features\", revise the bullet so the real tool appears naturally:\n\n\n```javascript\nBuilt PostgreSQL-backed reporting tables for weekly revenue dashboards.\n```\n\n\nThat is better than adding \"PostgreSQL\" to a long skills list with no supporting example.\n\n### Ask AI to critique before it rewrites\n\nAvoid starting with \"write my resume.\" A better prompt is:\n\n\n```javascript\nCompare my resume with this job description. Tell me which required skills\nare clearly shown, which are missing, and which are present but buried.\nDo not rewrite anything yet.\n```\n\n\nThis keeps you in control. You are using the tool to find gaps, not to produce a polished version that could sound like many other resumes.\n\n### Treat AI suggestions as rough drafts\n\nIf a bullet is weak, you can ask for a few options. Then rewrite the useful parts in your own words.\n\nBefore:\n\n\n```javascript\nWorked on backend APIs for customer workflows.\n```\n\n\nAn AI tool might suggest:\n\n\n```javascript\nDeveloped scalable backend APIs to streamline customer workflows and improve\noperational efficiency.\n```\n\n\nThat sounds polished, but it still says very little. A stronger human edit would be:\n\n\n```javascript\nBuilt three Spring Boot APIs for customer onboarding, reducing manual account\nsetup work for the support team.\n```\n\n\nThe final version is better because it says what was built, what technology was used, and who benefited.\n\n### Check the summary an AI tool produces\n\nAfter editing, ask the tool to summarize your resume for the target role:\n\n\n```javascript\nSummarize this candidate for a recruiter hiring for the job below. Use three\nsentences. Mention the strongest matches and any clear gaps.\n```\n\n\nRead the summary carefully. If it misses your strongest work, the problem may be your resume order, wording, or level of detail. Fix the resume, not just the summary.\n\n### Protect confidential information\n\nDo not paste confidential company data, internal project names, customer names, unreleased product details, or NDA-covered information into a public AI tool. Rewrite sensitive details at a safe level before using the tool, or skip AI for that section.\n\n### Fact-check every line\n\nAI tools can keep old numbers, add plausible details, or make a bullet sound stronger than the facts support. Before you send the resume, check every title, date, tool, metric, and claim.\n\nYou are responsible for every word on the page.\n\n\n```mermaid\nflowchart LR\n A[Job Description]:::input --> B[Extract role
requirements]:::process\n R[Your Resume]:::input --> C[Compare against
real experience]:::process\n B --> C\n C --> D[Add missing
true evidence]:::process\n D --> E[Check AI summary
for clarity]:::review\n E --> F[Human review
and fact-check]:::human\n F --> G[Final resume]:::pass\n\n classDef input fill:#00ceff,stroke:#000,color:#000\n classDef process fill:#ffa94d,stroke:#000,color:#000\n classDef review fill:#ffd43b,stroke:#000,color:#000\n classDef human fill:#38d9a9,stroke:#000,color:#000\n classDef pass fill:#69db7c,stroke:#000,color:#000\n```\n\n\nThe workflow is simple: use AI to find gaps, then use your judgment to decide what is true, relevant, and worth adding. The final resume should sound like a capable person explaining real work.\n\n---\n\n# Vague AI Text vs Real Work\n\nAI-generated resume text often sounds confident while saying very little.\n\n**Before:**\n\n\n```javascript\nSoftware engineer with experience building web applications and working with\ncross-functional teams.\n```\n\n\nThis could describe thousands of candidates. It has no role, stack, project, scope, or result.\n\n**After:**\n\n\n```javascript\nBackend engineer with 4 years of payments experience. Built Go services for\ncheckout, refunds, and reconciliation using PostgreSQL and Kafka. Reduced\ncheckout failures by adding retries and better gateway error handling.\n```\n\n\n**Why the after version works:** It is plain, specific, and believable. A recruiter can understand the candidate quickly. An AI summary also has concrete material to work with.\n\nHere is the same problem in a LinkedIn About section. Marcus Rivera asks AI to write it from scratch.\n\n**Before:**\n\n\n```javascript\nI am a software engineer who enjoys building applications and working with\nteams to solve technical problems.\n```\n\n\nThe wording is clean, but it does not tell a recruiter what Marcus actually does.\n\n**After:**\n\n\n```javascript\nI work on payments backend systems at a fintech in Austin, mostly in Go and\nPostgreSQL. Last year I helped move reconciliation jobs from a nightly batch\nprocess to an event-driven workflow. I am looking for backend roles where\nreliability and data correctness matter.\n```\n\n\n**Why the after version works:** Marcus gives the recruiter a real job context, a technical area, and a clear direction. It sounds like a person who understands his work.\n\nOne more example for a new graduate. Priya Sharma has no internships, so the AI tool fills the space with general claims.\n\n**Before:**\n\n\n```javascript\nComputer science graduate with experience building applications through\ncoursework and personal projects.\n```\n\n\n**After:**\n\n\n```javascript\nComputer science graduate focused on backend development. Built a Spring Boot\nexpense tracker with login, PostgreSQL storage, monthly reports, and a small\nadmin dashboard. Looking for entry-level backend or full-stack roles.\n```\n\n\n**Why the after version works:** Priya does not inflate her experience. She states her level, her project, the stack, and the kind of role she wants. That is stronger than a paragraph of broad adjectives.\n\n---\n\n# Where AI Use Backfires\n\nThe same tools that sharpen a resume can weaken it when you hand over too much judgment. The first item below does the most harm, because a resume the AI wrote end to end reads like the hundreds of others built the same way, and the claims it invents are the ones you cannot defend when an interviewer asks about them.\n\n- **Letting AI write the resume from scratch.** The result often sounds smooth but similar to many other resumes. Use AI for feedback and options, then write the final version yourself.\n- **Adding skills because the tool suggested them.** If you cannot explain where and how you used a skill, do not put it on the resume.\n- **Treating a fit score as a hiring decision.** A score can reveal gaps, but it is not the same as a recruiter or hiring manager reviewing your background.\n- **Copying the job description into your resume.** Using true terms from the posting is helpful. Copying unsupported language makes the resume less credible and can hurt you in interviews.\n- **Accepting invented metrics.** If AI suggests \"improved performance by 40%\" and you do not know where that number came from, delete it.\n- **Putting confidential information into prompts.** Do not paste internal metrics, customer names, unreleased product details, or NDA-covered material into public tools.\n- **Keeping phrases just because they sound professional.** Broad phrases like \"worked with teams\", \"built applications\", and \"solved technical problems\" do not help unless they are backed by real details.\n- **Skipping the final human read.** Read the resume as if a hiring manager will ask about every line. If you cannot defend it in an interview, it should not be there.","pageType":"job-search"}

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