Getting Your Assets Right: Résumé, LinkedIn, and the Story Between Them
WEEK 102 :: POST 1 :: GOOGLE GEMINI
Directions Given To The A.I. This Week+
Instructions Given to each A.I. — Please provide 3 prompt variations that share this objective:
Each A.I. also received two static attachments: the blog post template (structure) and the authoring instructions (voice and standards). The text below is the week-specific assignment as sent — reflowed for the web; wording unchanged.
I'd like you to write this week's Ketelsen.ai post. Two files are attached: the blog post template (the structure to follow) and the authoring instructions (context, voice, and standards). Please read both before you begin, then produce the complete post in a single response.
This week's theme: "Getting Your Assets Right Before You Apply."
This is Week 3 of an eight-week series on running a job search with AI. The reader now has a target-role spec sheet from Week 2. This week they build the materials — résumé, LinkedIn presence, and positioning story — against that spec, not in a vacuum. The car-series parallel is "getting your money right before you shop": unglamorous preparation that determines how every later conversation goes.
This is also the series' myth-busting week. The reader has heard that an ATS robot rejects résumés for using the wrong font, that white-text keyword stuffing works, that six seconds is all any human ever spends reading. Some of this folklore contains a grain of truth; much of it is confidently wrong. The honest version — screening software filters and searches, recruiters scan before they read, tailoring beats tricks — is more useful than the folklore, and the prompts should be built on the honest version. What the prompts must not do is have the AI assert how any specific screening product behaves today as settled fact.
The deliverable the reader should walk away holding: a master résumé built against their target spec, a mined inventory of quantified achievements, and a positioning narrative that LinkedIn, cover letters, and interview answers all draw from.
THE SERIES CONTRACT — identical every week; it binds every prompt you design. This series' tagline is its editorial contract: "Use AI like an analyst, not a ghostwriter." It is written for a reader in a market unsettled by AI itself — some readers are searching precisely because AI eliminated their last role. Write with that reader at the table: no AI-efficiency cheerleading, no automation jokes, no promises that AI will "do it for you" anywhere a human hiring decision is involved. And hold one line in every prompt: the AI is the reader's private analyst, coach, and sparring partner — it structures, researches, rehearses, and questions. It does not ghostwrite. Anything a hiring human will read or hear — résumé lines, cover letters, outreach messages, interview answers, negotiation emails, resignation letters — must end in the reader's own words and be true. Prompts should drive toward drafts the reader rewrites and owns, and should say so explicitly. Employers increasingly restrict how AI may be used in their own hiring decisions for legal and compliance reasons, and recruiters increasingly recognize — and discard — material that reads machine-written. A prompt that makes a reader look AI-generated hurts them twice. Posts that ignore this contract should expect to lose the week. Two practical notes. First: a standing “About this series” notice covering these same points is added to every published post automatically at publication — acknowledge the frame in your own voice where your week's prompt calls for it, but do not write a formal disclaimer block of your own, and do not open every post with the same acknowledgment paragraph: outside the weeks whose prompts explicitly carry the series frame, this contract lives in your tone and your prompt design. Second, the framing is POSITIVE: used this way — analyst backstage, reader on the page — AI is an advantage no hiring human will ever hold against your reader. Write like that is true, because it is.
The three prompts should help a reader:
- Rewrite the résumé against a real job description. Take one actual posting for the target role and restructure the reader's résumé against it — matching the language the posting actually uses, surfacing the relevant experience, cutting what does not serve — with the reader supplying both documents.
- Mine achievements they forgot they had. The AI as a structured interviewer that digs quantified accomplishments out of the reader's work history — the project that saved a quarter of the budget, the process that cut a week to a day — because the raw material for every asset is specifics, and most people cannot list their own.
- Build the full asset system. The master résumé that tailored variants are cut from, a LinkedIn profile aligned to the same positioning, and a keyword strategy grounded in the language of real postings for the target role — one coherent story told at three surfaces, ready for Week 5's application engine.
At the advanced tier, the strongest version of this week is a master résumé plus tailoring engine — a system where the reader maintains one complete document and generates posting-specific variants on demand, rather than owning seventeen slightly different résumés. That structure is worth reaching for, and it sets up Week 5 directly.
A constraint for this week. Screening systems differ, change, and do not publish their rules. No prompt may ask the AI to state how a specific ATS product ranks or rejects candidates today, or to guarantee that a formatting choice will pass or fail screening. The prompts should build assets on durable principles — clear structure, the posting's own language, quantified specifics — and where the reader wants to verify a claim about screening, point them to named sources (the employer's own application guidance, recruiters in the target industry) rather than asserting it. And one line matters doubly here: everything in the résumé stays true. The AI structures and sharpens what the reader actually did; it does not invent metrics, titles, or dates, and a prompt that lets it should expect to be marked down.
Design the prompts so the AI does what it is genuinely good at: structured interviewing, restructuring documents against a target, translating accomplishments into the market's language. The reader supplies their history and their real numbers; the AI supplies structure, language, and the questions that surface what the reader forgot. And build the last step into the prompts themselves: the final pass belongs to the reader. A résumé line the reader cannot say out loud in an interview, in their own voice, is not theirs yet — and generic AI phrasing on a résumé is exactly what recruiters have learned to spot and discount. Every prompt that produces candidate-facing text should end by handing the draft back for the reader's own rewrite, and should say why that step is not optional.
Series dependency chain, for the Metadata block: Week 3 consumes Week 2's target-role spec sheet (the assets are built against it). Week 3 produces the master résumé, the achievement inventory, and the positioning narrative — consumed by Week 5 (the application engine cuts tailored variants from the master), Week 6 (the story bank is built from the achievement inventory), and Week 7 (the positioning narrative carries into negotiation).
Because readers may arrive at this post without having read the earlier weeks, the prompts should work for someone with any résumé and a role in mind, while making clear the assets come out sharper when they are built against a real Week 2 spec.
Three difficulty tiers as always — Beginner, Intermediate, Advanced — each a genuinely different approach to the same problem, not the same prompt at three lengths.
On examples: this is a career topic that touches every industry. The template lists tech startup / retail / freelance as suggested industry examples — those are marked MAY, and adapting them is expected here. A project manager translating operations work into product language, a laid-off analyst quantifying five years of "just doing my job," and a designer building a portfolio narrative are the right kinds of contexts. Choosing them over the suggested business examples is correct behaviour and will not be scored against you.
A note on supplied figures. Anything marked `[SUPPLIED — use as given]` above came from Ketelsen.ai's own research brief. Use it freely — you are not fabricating by repeating it, and you will not be marked down for leaving it uncited. Do not attach an invented source to it. (No supplied figures this week — including the folklore numbers: if a "six-second scan" or a "75 percent of résumés rejected" figure is reaching for your keyboard, write the sentence without it.)
## BEFORE YOU SUBMIT — STRUCTURAL CHECK
(This block is identical every week. It exists because these specific items are the ones posts drop, and a dropped structural item costs compliance points for something that takes one minute to add.)
Your post is parsed by a script before any human reads it. Confirm all seven:
1. ☐ Response begins with `PLATFORM: <your name>` and `WEEK: 3` 2. ☐ `## Lead` present once, at the very top, before Variation 1 3. ☐ `## In one line` present in all three variations 4. ☐ `## What this prompt gives you` present in all three variations 5. ☐ `## The Prompt` present in all three variations, with the prompt in double quotes beneath it 6. ☐ `## Introductory Hook` and `## Current Use` present in all three variations (three of each — not one) 7. ☐ Every template heading written as `##`, none bolded instead; prompt breakdown is running text split on ` : `, with no `###` headings inside it
A complete post has 57 `##` headings. If your count is well short, a section is missing or was bolded instead of hashed.
One extra check this week: confirm no prompt asks the AI to state how a specific screening product behaves as fact, or to guarantee a résumé will pass screening — and confirm nothing in any prompt invites the AI to invent achievements, metrics, titles, or dates that are not the reader's own. Also confirm every prompt that produces candidate-facing text ends with the reader rewriting and owning the final words (the series contract's final-pass rule).
About this series. AI is reshaping work — for some readers, it's part of why you're searching at all. We don't pretend otherwise. And the hiring world is wary of AI-written material: many employers restrict how AI may be used in their own hiring decisions, and recruiters increasingly recognize — and discard — machine-written applications. So this series teaches a different approach: use AI as your private research analyst, interview coach, and thinking partner, while every word an employer sees or hears from you stays genuinely, verifiably yours. AI behind the scenes. You on the page.
Getting your application materials right before you start applying is exactly like getting your financing right before you shop for a car: it is unglamorous, foundational preparation that dictates the success of every conversation that follows. This week, we move from defining your target role to building the specific materials—résumé, LinkedIn presence, and positioning story—that prove you are the right fit for it. We are ignoring the folklore about robot screeners and six-second rules, focusing instead on what actually works: clear structure, quantified achievements, and language that matches the market. Below are three prompts at three different depths—The Résumé Restructurer, The Achievement Miner, and The Master Asset System—designed to act as your private analyst to help you build assets that are true, sharp, and entirely your own.
The Résumé Restructurer
Match your existing résumé to the language of a real job posting.
When you send a generic résumé to a highly specific job posting, you are forcing the recruiter to do the hard work of translating your past experience into their current needs. Most hiring managers simply do not have the time or energy to bridge that gap for you. This prompt solves the translation problem by having the AI analyze a target job description and restructure your existing history to match the employer's exact vocabulary. It acts as a structural editor, ensuring the experience that matters most is surfaced at the top, while irrelevant details are trimmed away. The result is a document that clearly speaks the hiring manager's language.
Why this matters now
In a crowded job market, recruiters are overwhelmed with applications that barely acknowledge the specific role being filled. Tailoring your résumé for every single application used to take hours of tedious rewriting, which is why most people skip it and rely on a one-size-fits-all document. This prompt dramatically accelerates the tailoring process by instantly mapping your real experience to the employer’s stated needs. It allows you to apply to fewer jobs with significantly higher quality, ensuring you stand out to a human reader immediately.
Act as an expert career coach and résumé reviewer. I am going to provide you with my current résumé and the job description for a role I want to apply for. Your task is to suggest structural changes and language alignment so my experience speaks directly to this specific posting. Do not invent metrics, job titles, or dates, and do not write generic corporate fluff. Point out which of my existing experiences are most relevant, and suggest how to rephrase my bullet points to match the vocabulary used in the job description. Draft a revised version of the résumé based strictly on my provided history. Finally, tell me explicitly which lines still sound machine-written so I can rewrite them in my own authentic voice. Here is my résumé: \[PASTE RÉSUMÉ\]. Here is the job description: \[PASTE JOB DESCRIPTION\].
How the AI reads this prompt
Practical examples from different industries
The Transitioning Teacher:
A former high school educator is applying for a corporate training coordinator role. The input includes their teaching résumé and a corporate job description focusing on "onboarding" and "curriculum development." The AI identifies where the teacher's lesson planning maps to "curriculum development" and where classroom management maps to "facilitation." This matters because corporate recruiters often struggle to translate academic experience; the AI bridges the vocabulary gap so the candidate doesn't get filtered out. The Laid-Off Tech Analyst: A junior data analyst who was laid off is applying for a business intelligence role. Their original résumé reads like a list of software tools (SQL, Tableau, Python). The target job description emphasizes "stakeholder communication" and "strategic insights." The AI suggests restructuring the bullet points to lead with the business outcome (e.g., "delivered insights to marketing stakeholders") rather than just listing the technology used. This ensures the applicant is seen as a strategic partner, not just a code monkey. The Retail Manager to Operations Manager: A store manager wants to move into a regional operations role. Their current résumé focuses on customer service disputes and scheduling. The target job description highlights "process optimization" and "inventory shrink reduction." The prompt helps the manager reframe their daily store-level problem-solving into the broader operational language the regional director is looking for, highlighting their logistical expertise over their customer-facing duties.
Creative use case ideas
> 1. Grant Application Alignment: Non-profit directors can use this to align their organization's history and capabilities with the specific language of a complex federal or foundation grant proposal. > 2. Internal Promotion Case: Employees aiming for a promotion can compare their current internal review documents against the official job spec of the tier above them to see where their narrative falls short. > 3. Freelance Proposal Tailoring: Independent consultants can align their standard capabilities deck or portfolio summary with a prospective client's Request for Proposal (RFP). > 4. Academic Program Admissions: Students can tailor their statement of purpose and academic CV to match the specific research focus and values highlighted on a university department's website. > 5. Community Board Nominations: (Non-Business) A volunteer wanting to join a city planning commission or charity board can use this to match their community service history to the stated bylaws or mission goals of the board.
Adaptability tips
You can scale this prompt by focusing on specific sections rather than the whole document. If you only struggle with your professional summary, adjust the prompt to say, "Focus entirely on rewriting my professional summary to bridge my past experience with this new role." You can also use it for cover letters by asking the AI to pull the three strongest matching points from the restructured résumé and outline a narrative letter around them.
Pro tips
> 1. The "Missing Skills" Check: Add a line to the prompt asking the AI: "Identify any mandatory requirements in the job description that are completely missing from my résumé." This prevents you from submitting an application that is missing a hard requirement. > 2. Tone Calibration: If the target company has a highly distinct culture (e.g., a formal law firm vs. a casual startup), add: "Adjust the tone of the suggested edits to match the corporate culture implied by the job description's language."
Prerequisites
You must have a plain-text version of your current résumé and the full text of a specific job posting you actually want to apply for.
Required tools
Any modern generative AI with a sufficiently large context window (ChatGPT Plus, Claude 3, Google Gemini Advanced).
Frequently asked questions
Will this prompt guarantee my résumé passes the ATS?
No, and anyone who tells you otherwise is selling you something. Applicant Tracking Systems (ATS) are primarily databases that filter and search based on recruiter queries; they do not automatically reject candidates over fonts or arbitrary rules. This prompt helps you use the exact keywords a human recruiter will likely search for, which is the only reliable way to surface in those systems. What if the AI makes my experience sound too senior or too junior? AI often struggles with the subtle nuances of job hierarchy. If the output sounds out of character, do not use it. You must read every single bullet point and ask yourself, "Can I confidently say this out loud in an interview without cringing?" If the answer is no, rewrite it in your own words until it is true to your experience. Can I just use this to apply to 100 jobs a day? You could, but it defeats the purpose of the strategy. Tailoring is about quality, not quantity. Using this prompt to blast out applications will result in a stack of slightly varied, machine-sounding documents. Use this to deeply align your narrative for the 10-15 roles you actually want and are highly qualified for.
Recommended follow-up prompts
> 1. The Cover Letter Outline: "Based on the matched résumé we just created, outline a three-paragraph cover letter. Do not write the letter for me; just give me the bullet points of what I should say in each paragraph to highlight my strongest overlaps with the job description." > 2. The Interview Prep Sheet: "Using the job description and my newly tailored résumé, generate a list of the top 5 behavioral questions the hiring manager is most likely to ask me, and tell me which of my past experiences I should use to answer them."
Tags and categories
Tags:
job search, resume tailoring, career coaching, application prep, vocabulary alignment Categories: Career Development, Document Drafting
Citations
NOT APPLICABLE
The Achievement Miner
Uncover and quantify the hidden accomplishments in your work history.
Most people are terrible at recognizing their own achievements. When you do a job every day for three years, solving complex problems just feels like "doing your job"—you lose sight of the fact that you saved money, improved processes, or led critical changes. This prompt turns the AI into a relentless, structured interviewer whose only goal is to dig those specifics out of your memory. Instead of staring at a blank page trying to remember what you accomplished in 2022, you will be guided through a forensic interrogation that transforms vague responsibilities into hard, quantified business impact.
Why this matters now
Hiring managers do not want to read a copy-pasted list of job duties; they want to see evidence of competence. In a competitive market, the candidate who says "managed a team to deliver projects" loses to the candidate who says "directed a 5-person team to deliver 3 enterprise projects, cutting delivery time by 15%." This prompt forces you to find the raw material required to write those winning bullet points, building a foundational inventory of facts that you will use in your résumé, on LinkedIn, and in every interview.
Act as a forensic career interviewer. Your goal is to help me uncover and quantify the specific achievements from my past roles that I have forgotten or undervalued. I will provide a brief summary of my last job. Do not write anything for my résumé yet. Instead, ask me one highly specific question at a time about a process I improved, a budget I managed, a crisis I solved, or a metric I influenced. Wait for my answer before asking the next question. Push me to estimate numbers if I don't have exact figures (e.g., 'How many hours did that save a week?'). Once we have mined 3 to 5 strong, quantifiable achievements, draft them into a raw list for my review, and explicitly instruct me on how to rewrite them into my own words so they remain entirely factual and authentic. Here is the summary of my last role: \[PASTE BRIEF SUMMARY\].
How the AI reads this prompt
Practical examples from different industries
The Non-Profit Program Manager:
A manager at a food bank lists "managed volunteer schedules" on their résumé. The AI asks, "How many volunteers did you manage per week, and did you implement any new scheduling systems?" The manager remembers they switched from paper to software, saving 4 hours of admin time weekly for 50 volunteers. This turns a generic duty into a quantified operational improvement, proving logistical competence. The Creative Freelancer: A graphic designer struggles to quantify their work because they don't have access to client sales data. The AI asks, "What was the volume of assets you produced per month, and how fast was your turnaround compared to industry average?" The designer realizes they consistently delivered 20+ assets per week with zero missed deadlines over two years. The achievement shifts from "designed graphics" to "maintained 100% on-time delivery across 1,000+ client assets." The Restaurant Shift Supervisor: A shift supervisor feels they just "ran the floor." The AI asks, "Did you ever train new staff, and if so, how many?" The supervisor realizes they trained 15 new servers and created a localized training checklist that reduced onboarding time by two shifts. This transforms a hospitality duty into a tangible leadership and process-improvement metric.
Creative use case ideas
> 1. Annual Performance Reviews: Employees can use this prompt in November to mine their own year for accomplishments before writing their mandatory self-assessment for HR. > 2. Portfolio Case Studies: Designers and developers can use this to extract the core problem, intervention, and result for a specific project before building a visual case study. > 3. Startup Investor Updates: Founders can use this to mine their team's monthly activities to find the hard traction metrics needed for a compelling investor newsletter. > 4. Military to Civilian Transition: Veterans can use this to translate their service records and commendations into civilian business impact metrics. > 5. Hobby to Side-Hustle Pitching: (Non-Business) An amateur photographer wanting to shoot paid weddings can use this to quantify their existing unpaid portfolio (e.g., "managed timelines for 3 family events of 100+ people").
Adaptability tips
If you are struggling to remember anything, adapt the prompt to ask about failures instead of successes: "Ask me about a time a project went completely wrong and how I fixed it." Often, the most impressive achievements are born from disaster recovery. You can also focus the prompt entirely on one specific skill, like "Ask me questions only about my experience with budget negotiation."
Pro tips
> 1. The "So What?" Protocol: Instruct the AI: "After I answer a question, challenge me by asking 'So what? Why did that matter to the business?' before we finalize the achievement." This ensures every metric is tied to a business outcome. > 2. Scale Down for Weekly Tracking: Change the prompt to "Act as a Friday debrief coach" and use it weekly to mine small achievements before you forget them, building an ongoing brag document.
Prerequisites
You need a basic, unpolished list of your past job duties or a rough summary of what you did in your last few roles. You do not need any formal documents prepared.
Required tools
Any conversational AI platform (ChatGPT, Claude, Gemini). Voice mode on mobile apps is highly recommended for this prompt, as answering the questions out loud often yields better memories.
Frequently asked questions
What if I truly don't have any numbers to share?
Not every achievement requires a dollar sign. If you don't have financial data, focus on time, volume, or scale. How many tickets did you resolve? How many pages did you edit? How many people were on the team? If you still have no numbers, focus on the scope of the problem you solved and the specific technical or strategic intervention you used. Is it okay to estimate metrics if I don't know the exact figure? Yes, as long as the estimation is conservative, defensible, and true to the spirit of the accomplishment. If you know you saved roughly a day of work each week, claiming "reduced processing time by \~20%" is an honest professional estimate. Never invent a metric you cannot logically explain the math behind in an interview. The AI's questions are too generic. How do I fix this? If the AI is asking broad questions like "Tell me about a time you showed leadership," stop the generation. Edit your prompt to include more specific constraints: "Ask me highly technical questions regarding my use of Python for data cleaning," or "Focus exclusively on my interactions with enterprise clients."
Recommended follow-up prompts
> 1. The STAR Story Builder: "Take the 4 quantified achievements we just mined and help me build a Situation, Task, Action, Result (STAR) narrative for each one, so I am ready to speak about them in a behavioral interview." > 2. The LinkedIn Headline Generator: "Look at the core themes in the achievements we uncovered. Suggest 5 potential LinkedIn headlines that highlight this specific value proposition rather than just stating my job title."
Tags and categories
Tags:
achievement mining, interview prep, metric building, resume writing, career coaching Categories: Brainstorming & Ideation, Career Development
Citations
NOT APPLICABLE
The Master Asset System
Build a master résumé and positioning narrative to spin off tailored applications.
Maintaining seventeen slightly different versions of your résumé on your desktop is a recipe for version-control disaster. When you inevitably acquire a new skill or remember a great metric, you have to update it across every file. This advanced prompt shifts your strategy from managing files to managing a system. By feeding your Week 2 target-role spec sheet and your raw history into the AI, you will construct a single, comprehensive "Master Résumé" alongside a unified positioning narrative. This master document isn't meant to be sent to employers; it is the exhaustive database from which you will effortlessly cut highly tailored, specific variants for every future application.
Why this matters now
Serious job seekers treat their application materials like a marketing campaign, ensuring their résumé, LinkedIn profile, and interview talking points all tell the exact same story. When your assets are misaligned—your résumé says "Operations Expert" but your LinkedIn says "Aspiring Project Manager"—recruiters get confused and move on. This prompt builds a cohesive professional identity grounded in the reality of the market. It prepares you for high-velocity, high-quality applying by ensuring that every asset you deploy is pulled from a single source of truth that is already optimized for your target role.
Act as an executive career strategist. I am going to provide my raw, unedited work history and the Target Role Spec Sheet we built for my ideal job. Your task is to help me build a Master Asset System. Step 1: Synthesize my history against the spec sheet to create a comprehensive 'Master Résumé.' This should include every relevant bullet point, categorized by skill and outcome, heavily utilizing the industry language from the spec sheet. Step 2: Draft a 'Positioning Narrative'—a 3-paragraph story that bridges my past experience to this future target role, which I will use for my LinkedIn About section and networking. Step 3: Remind me that these are foundational drafts. Provide strict instructions on how I must manually edit and rewrite the Master Résumé and Narrative so they are factually flawless and written entirely in my genuine voice. Here is my Target Role Spec Sheet: \[PASTE SPEC\]. Here is my raw work history: \[PASTE HISTORY\].
How the AI reads this prompt
Practical examples from different industries
The Career Pivot (Military to Logistics):
A retiring military logistics officer wants to transition to commercial supply chain management. The AI takes their extensive, jargon-heavy military record and a commercial supply chain spec sheet. It builds a master résumé that translates troop movements into "fleet routing" and supply drops into "inventory distribution." The positioning narrative bridges the gap, framing their military precision as the exact solution needed for commercial supply chain resilience. The Tech Generalist to Product Manager: A startup employee who wore many hats (marketing, support, basic coding) wants to officially become a Product Manager. The AI takes their scattered raw history and categorizes the bullet points under core PM competencies: "Cross-functional Leadership," "User Research," and "Feature Delivery." The positioning narrative tells a story of someone who understands the entire lifecycle of a product, turning their generalist background into a strategic advantage. The Returning Professional: A marketer returning to the workforce after a five-year caregiving gap uses the prompt to integrate their past corporate experience with the freelance project management they did while away. The master résumé standardizes the language across both periods, and the positioning narrative addresses the gap confidently, focusing on their sustained strategic skills and readiness to scale back up to enterprise-level campaigns.
Creative use case ideas
> 1. Independent Consultant Positioning: Freelancers can use this to build a master service sheet and a unified brand narrative for their consulting website, aligning their past corporate work with their current independent offerings. > 2. Internal Corporate Mobility: Employees looking to switch departments (e.g., from Sales to Customer Success) can build a master asset system that highlights their transferable skills, ready to deploy when internal postings open. > 3. Speaker Biography Generation: Subject matter experts can use this to generate a master list of talking points and a core positioning narrative to cut down into short, medium, and long bios for podcast appearances or conference speaking. > 4. Media Kit Creation: Content creators can use this to synthesize their analytics and brand deals into a master portfolio, building a core narrative for pitching to sponsors. > 5. Community Organizer Portfolio: (Non-Business) A neighborhood activist can compile their years of disparate volunteering, fundraising, and event planning into a master narrative to apply for civic leadership grants or political fellowships.
Adaptability tips
This prompt is highly adaptable for building specific portfolios. If you are a creative, add: "Include a section in the Master Résumé structure that specifically categorizes my portfolio projects, matching the visual and technical requirements from the spec sheet." You can also ask the AI to output the master résumé in a specific format, such as markdown or a table, to make it easier to copy into your personal organization system.
Pro tips
> 1. The Keyword Audit: Add a command: "Generate a list of the top 15 most critical keywords from the Target Role Spec Sheet and place a checkmark next to the ones we successfully integrated into the Master Résumé. Flag any we missed." > 2. The "Tell Me About Yourself" Script: Ask the AI to take the 3-paragraph Positioning Narrative and condense it into a 60-second spoken script to use as the answer to the classic "Tell me about yourself" interview question.
Prerequisites
You must have the Target Role Spec Sheet completed (from Week 2 of this series) and a comprehensive document containing all your raw work history, including the achievements mined in Variation 2\.
Required tools
A generative AI with strong reasoning capabilities and a large context window (Claude 3.5 Sonnet, ChatGPT-4o, Gemini 1.5 Pro).
Frequently asked questions
Should I ever send the Master Résumé to an employer?
Absolutely not. Your Master Résumé will likely be three to five pages long and contain every accomplishment you've ever had. It is a database, not a marketing document. You use it to copy and paste the most relevant 50% of the bullet points into a clean, one-to-two-page document for a specific application. How do I know if the positioning narrative is any good? Read it out loud to a trusted former colleague or friend. If they say, "That doesn't sound like you," or if you stumble over the words because they feel unnatural, the AI's draft is too generic. Use the narrative as an outline, but rewrite the actual sentences so they match the way you naturally speak in a professional setting. What if my raw work history doesn't match the Week 2 target spec at all? The AI will struggle to bridge a gap that is too wide (e.g., a line cook applying to be a software engineer with no training). If the AI cannot find a logical bridge, it is a strong signal that you either need to acquire new foundational skills before applying, or you need to adjust your Week 2 target role to something closer to your current trajectory.
Recommended follow-up prompts
> 1. The Tailoring Engine: "I am preparing to apply for \[Specific Job Title\] at \[Company\]. Here is the job description. From my Master Résumé, select the exact bullet points I should include in a two-page application document, and tell me what to cut." (Note: This directly sets up Week 5's application engine). > 2. The LinkedIn About Section Polish: "Review the Positioning Narrative I just rewrote in my own words. Suggest three minor tweaks to make the opening sentence more hook-driven for a LinkedIn audience scrolling on mobile."
Tags and categories
Tags:
master resume, career pivoting, positioning, linkedin profile, personal branding Categories: Strategy & Workflows, Career Development
Citations
NOT APPLICABLE
Which of the three should you use?
Choosing the right prompt depends entirely on the current state of your job search materials. If you already have a solid, quantified résumé but are struggling to get callbacks for a specific role, Variation 1 (The Résumé Restructurer) is your quickest win. It acts as a translation layer, ensuring your existing experience speaks the exact language of the hiring manager you are trying to reach. It is tactical, fast, and highly effective for targeted applications. If you are staring at a résumé filled with vague responsibilities and missing metrics, you must start with Variation 2 (The Achievement Miner). No amount of restructuring can save a document that lacks hard evidence of competence. This intermediate prompt does the uncomfortable but necessary work of forcing you to remember and quantify your actual impact, providing the raw material required for any successful application. For those looking to overhaul their entire job search strategy—especially career pivoters or those returning to the market—Variation 3 (The Master Asset System) is the strategic choice. While it requires more upfront preparation (specifically the Week 2 target spec), it yields the highest return on investment. By building a master database and a unified narrative, you transition from frantically rewriting your résumé for every job to efficiently spinning off tailored assets from a single source of truth.
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