jobhacki.com · @jobhacki
Download PDFFree with a JobHacki account
JobHackiOpportunity Guide
⚡ Premium Action Guide

Resume Template Playbook — Build once, tailor fast

Create a clean master resume, tailor it to any job in minutes (manually with AI or fully automated), and manage outreach without fluff or guesswork.

📌 Updated for 2026 🧾 ~$0.02 Approx. AI cost per tailored resume (source-reported) 📣 @jobhacki · JobHacki Community
🚀
Start FastClear first steps you can take this week.
📋
Real SourcesBuilt from people who actually did it.
💰
Honest NumbersSource-reported pay, costs, and risks.
Get the Full Guide Vault →
🔒 Includes checklists, scripts & source-backed insights
YOU WILL LEARN
What you'll build
Platforms & tools
Step 1 — 🎯 Define your target role
Step 2 — 🧭 Choose your build path
Step 3 — 🧱 Build your master resume skeleton
Step 4 — ✍️ Write outcome‑focused bullets

What you'll build

A one-page, ATS-friendly master resume you can duplicate and tailor for each role in minutes. Choose a manual AI path (ChatGPT or Claude) or an automation path (Make.com or n8n) that scrapes job posts, extracts keywords, rewrites targeted bullets, and logs everything in Google Sheets and Docs.

You’ll also get prompts, outreach scripts, and a lightweight workflow to research companies and follow up strategically.

  1. One master resume in clean Markdown → Google Doc
  2. Manual AI tailoring or full automation (Make.com/n8n)
  3. Keyword extraction + fit scoring + saved variants
  4. Job tracker in Google Sheets with resume links
  5. Targeted outreach emails/DMs that get replies

Platforms & tools

Website Builders0 free · 2 paid
AI Models2 free · 3 paid
Dev & Hosting0 free · 2 paid
Automation1 free · 3 paid

Step 1 — 🎯 Define your target role

Pick the exact title, level, and industry you’re aiming for. Collect 3–5 recent postings and highlight core responsibilities, must-have tools, and repeated keywords. Research each company’s mission and team on LinkedIn to understand their language and priorities.

Tip

Employers scan in an F-pattern: top summary → first bullet line → down the left. Front‑load your top skills and proof. On LinkedIn, keep it tight—overstuffing makes you look overqualified or off‑target.

LinkedIn — where you'll do this

LinkedIn — where you'll do this

Step 2 — 🧭 Choose your build path

Pick a manual AI path for speed and control, or an automation path to batch-tailor resumes from public postings. Use the table to start on your chosen platform.

PlatformWhat to do in this step
Make.comCreate two scenarios: (1) Run Apify Indeed scraper; (2) Watch for completion, extract keywords, tailor resume with OpenAI module, save to Google Docs, log to Google Sheets.
n8nCreate a workflow: Apify node to scrape → OpenAI node to tailor → Google Docs/Drive to store → Google Sheets to track. Add a separate AI screening node for fit scores.
ChatGPTPaste job post + your master resume, run the tailoring prompt (below), get Markdown, paste into Google Docs.
ClaudeSame as ChatGPT: paste job + resume, run tailoring prompt (below), export Markdown to Google Docs.
Google DocsKeep one master resume; duplicate per job. Use consistent style and headings; keep a shareable link in your tracker.
Tip

Constrain AI to small, well-defined edits (summary, skills, 3–6 bullets). Don’t ask one agent to do everything—quality drops.

Google Sheets — where you'll do this

Google Sheets — where you'll do this

make.com — where you'll do this

make.com — where you'll do this

Google Docs — where you'll do this

Google Docs — where you'll do this

n8n — where you'll do this

n8n — where you'll do this

Step 3 — 🧱 Build your master resume skeleton

Create a clean, one-page master in Markdown so it converts nicely to Google Docs. Keep fixed section order and placeholders you’ll swap per job.

Template — Master resume (Markdown, ATS-friendly)
# [FULL NAME]
[City, ST] • [Email] • [Phone] • [LinkedIn] • [Portfolio/Loom]

## Target Role
[ROLE TITLE] — [Industry/Domain]

## Summary
[1–3 lines: years, standout strengths, relevant tools, 1–2 proof metrics]

## Skills
- [Skill/Tool 1] • [Skill/Tool 2] • [Skill/Tool 3] • [Skill/Tool 4] • [Skill/Tool 5]

## Experience
### [Company] — [Title], [Dates]
- [Action] using [Tool/Method] to [Solve X for Y], resulting in [Outcome %/time/$]
- [Action] for [Audience/Function]; improved [Metric] by [Number].
- [Action]; reduced [Cost/Risk] by [Number] via [Approach].

### [Company] — [Title], [Dates]
- [3–4 targeted bullets following the same formula]

## Projects (if applicable)
- [Project] — what you built, how, result/metric, link.

## Education & Certifications
- [Degree], [School] — [Year]
- [Certification], [Issuer] — [Year]
Tip

Keep the structure fixed and let AI fill only Summary, Skills, and Bullets. Use ATX headings (#, ##) for clean Google Doc conversion. Manually sort the most relevant roles/sections to the top if you’re pivoting. A vertical skill list at the top triggers a quick “check‑mark” scan.

Step 4 — ✍️ Write outcome‑focused bullets

Use one formula for every bullet: Action + Tool/Method + Problem/Scope + Result + Metric. Keep verbs strong, nouns specific, and results measurable.

Template — Bullet builder
- [Owned/Built/Led/Improved] [What] using [Tool/Method] to [Solve X for Y], resulting in [Metric %/#/$] within [Timeframe].
Tip

Replace vague lines like “Did SOC labs” with specifics (what logs, which playbooks, what you found). Many companies train their stack—highlight fast learning and accuracy. If you can’t articulate metrics, you’re invisible. Add recognized contributions (e.g., open source) when relevant.

Step 5 — 🔎 Build a keyword bank from postings

Scan 3–5 postings for repeated skills, tools, and domain phrases. Add synonyms and acronyms. Map each keyword to a section (Summary, Skills, specific role bullets) so tailoring is deliberate.

Prompt — Extract keywords from a job post
You are an ATS keyword extractor. Return JSON only with keys: {"must_have":[],"nice_to_have":[],"domain_terms":[],"soft_skills":[],"metrics_hinted":[]}.

Input Job Post:
[PASTE JOB DESCRIPTION]

Rules:
- De-duplicate; normalize synonyms (e.g., "Zendesk" vs "ticketing").
- Keep 5–12 items per array.
- Don’t add terms not found in the post.
Tip

Check location/legal restrictions early—some remote roles hire only in certain states. Include role‑specific terms (e.g., Zendesk, Intercom, HIPAA; Python, JSON, SQL) when applicable.

Step 6 — 🗂️ Set up your job tracker

Create a single Google Sheet to organize roles and link each tailored resume. This becomes your control center for outreach and follow-ups.

Template — Google Sheets columns
Position Name | Job Type | Company | Company Location | Description | URL | Customized Resume Link | Date Created | Posted At | Scraped At | First Name | Last Name | Email | Strengths | Weaknesses | Risk Factor | Reward Factor | Overall Fit | Justification | Status
Tip

Store any lead data (IDs, contacts, emails) in extra columns. Keep consistent naming so automations map cleanly.

Step 7 — 🤝 Tailor manually with AI (ChatGPT or Claude)

Use the master skeleton and run a focused tailoring prompt. Keep the structure; only swap Summary, Skills, and 3–6 most relevant bullets. Paste the Markdown output into Google Docs and save a shareable link in your tracker.

Prompt — Generic tailoring
Context: I am applying for [ROLE] at [COMPANY] in [INDUSTRY].
My master resume (Markdown):
[PASTE]
Job description:
[PASTE]

Task: Return only Markdown for a one-page resume. Keep headings and order. Edit Summary (2–3 lines), Skills (8–12 items), and the top 3–6 bullets to mirror the job’s language and measured outcomes. Preserve my truth; no fabrications. Keep verbs strong and metrics concrete. Avoid emojis/graphics.
Prompt — Career changer
You are an ATS-savvy resume editor.
Input: Master resume (Markdown) + Job post.
Goal: Reframe transferable skills. Move the most relevant experience/projects above older roles. Map each bullet to a requirement. Output strict Markdown in my original structure. Don’t invent employers or dates.

Highlight: domain knowledge I’ve built, fast learning, and 1–2 quantified wins relatable to the new role.
Prompt — Fresher/No experience
You are an entry-level resume editor.
Input: Education, projects, internships, volunteer work, and a job post.
Output: Markdown resume with Summary (degree, strengths, 1–2 achievements), Skills (tools learned), Projects (what, how, result), and Education. Replace job bullets with project bullets tied to the job’s keywords. Keep to one page. No fluff.
Prompt — Customer support
You are a CX resume editor.
Input: Master resume (Markdown) + Support role JD (e.g., Zendesk/Intercom, email/chat/phone support).
Task: Emphasize ticket volume, SLAs, CSAT, deflection, documentation, and tooling (Zendesk/Intercom/SSO/HAR/browser logs). Output Markdown only, one page, ATS-friendly.
Prompt — Cyber (SOC or GRC)
You are a cybersecurity resume editor.
Input: Master resume + SOC or GRC job post.
Task: SOC → emphasize alert triage, log analysis (Windows event, SIEM), phishing investigation, playbooks, EDR.
GRC → emphasize risk registers, control mapping (ISO 27001/Essential Eight), supplier reviews, policies.
Output one-page Markdown, measurable bullets, accurate tools, no fabrications.
Tip

Template most of your resume and let AI fill only small portions—this keeps results predictable and ATS‑safe.

Step 8 — ⚙️ Automate sourcing from public postings

Automate job collection for research and tailoring (not auto-applying). Configure Apify/Appify to pull basic fields and trigger your tailoring flow.

PlatformWhat to do in this step
Make.comScenario A: Apify actor → set search (e.g., title “data engineer”, location “San Francisco, United States”, max 10) → store dataset. Scenario B: Watch completion → send JD text to OpenAI module for tailoring → create Google Doc → add row in Google Sheets.
n8nAdd Apify node and API key → run Indeed bulk scraper task → once finished, pass results to OpenAI node → save tailored resume to Google Drive/Docs → append a row in Google Sheets.
AppifyUse marketplace scrapers; enable 'watch actor runs' to trigger only on new data instead of frequent polling.
Tip

Scrape for research/tailoring only. Avoid auto-applying on Indeed—violates terms and risks reputation.

Step 9 — 🔐 Connect credentials (Sheets, Docs, AI)

Authorize Google and your AI provider inside your automation platform. Then map outputs into Docs and Sheets cleanly.

PlatformWhat to do in this step
n8nGoogle Sheets: create new credentials → in Google Cloud Console: new project, enable Sheets API, configure OAuth consent, create Web App OAuth client, add n8n redirect URI, copy client ID/secret to n8n, publish and sign in. OpenAI: create and paste API key in OpenAI node.
Make.comAdd Google Sheets/Docs connections under Connections. Add OpenAI (or compatible) module with API key. Optionally sanitize text with a 'Set multiple variables' module before writes.
Tip

During Google OAuth you may see a warning—use Advanced → proceed if you trust your setup. Use a structured output parser (JSON schema) so strengths/weaknesses/fit score map into distinct columns.

Step 10 — 🧠 Build the tailoring + screening prompts (automation)

Treat GPT as an API: send JSON in, expect JSON out for reliable mapping. Use separate prompts for tailoring and for screening.

Template — Tailoring (system prompt)
You are an ATS-safe resume tailor. Keep structure fixed. Only update: summary (2–3 lines), skills (8–12), and 3–6 bullets to reflect the job’s language and results. Never fabricate companies/dates. Output JSON only: {"summary":"","skills":[],"bullets":[""],"keywords_matched":[],"warnings":[]}.
Template — Tailoring (user prompt)
{
  "job_post": "[JOB DESCRIPTION]",
  "master_resume_markdown": "[PASTE]",
  "must_have_keywords": ["[K1]","[K2]","[K3]"]
}
Template — Screening agent (fit rating)
System: Compare candidate resume to job description. Return JSON with fields: {"strengths":[],"weaknesses":[],"risk":"low|med|high","reward":"low|med|high","overall_fit":0-100,"justification":""}. Keep it concise and evidence-based.
User: {"job_post":"[PASTE]","resume_text":"[PASTE]"}
Tip

Better models yield cleaner mapping but cost more. Start small; upgrade only if outputs are noisy.

Step 11 — 📇 Extract your name and email reliably

Extract first name, last name, and email with a dedicated extractor node/module before AI tailoring so you can label files and rows consistently.

PlatformWhat to do in this step
Make.comAdd an information extractor module. Mark first_name, last_name, email as required. Route failures to a manual review path.
n8nUse an Extract/Parser node or a simple Function/Regex node to pull name/email from resume text; set required fields and a fallback route.
Tip

Don’t overload the AI agent with metadata parsing. Keep extraction separate for stability.

Step 12 — 🔁 Handle Word, PDF, and TXT resumes

Make your flow robust to different file types with branching extraction logic. Normalize to plain text before sending to AI.

PlatformWhat to do in this step
Make.comAdd a Switch module on mimeType → DOCX: convert to text; PDF: use PDF-to-text; TXT: pass through. Then merge back to a single path.
n8nUse a Switch node by file extension/mime → branch to appropriate extractor (e.g., Google Drive > Download + text converter). Rejoin for AI steps.
Tip

When working with Google Drive, use the correct nested file ID. A wrong ID breaks conversions.

Step 13 — 🧾 Write to Google Docs and log to Sheets

Combine the tailored fields back into your Markdown skeleton, convert to a new Google Doc, and paste its shareable link into your tracker along with screening results.

PlatformWhat to do in this step
Make.comAssemble Markdown → Create Google Doc → Append Google Sheets row (title, company, URL, tailored link, strengths, weaknesses, risk, reward, fit, justification).
n8nAssemble Markdown → Google Docs/Drive: create file → Google Sheets: append row with all mapped fields.
Tip

Use Markdown-to-Doc for clean headings/bullets. After the run, spot-check the Sheet for fit scores and links that open.

Step 14 — ⏱️ Add delays, retries, and stability

Introduce safe delays and retry logic to avoid rate limits and batching issues. Queue long waits outside your automation if needed.

PlatformWhat to do in this step
HookdeckHold webhook data for longer delays; configure retry intervals (e.g., 10m, 60m, 290m). Test by POSTing sample payloads.
Make.com / n8nUse Break/Retry (exponential backoff) and Ignore-on-error paths. Enable storing incomplete executions so you can resume.
Tip

Hookdeck can delay for days without extra databases. Log failures with context so you can replay cleanly.

Step 15 — 🧪 Test end‑to‑end and iterate

Run your flow with 2–3 postings. Verify extraction, AI outputs, Doc formatting, and Sheet logging. If a step fails, check the most recent execution, fix mappings, and rerun. Add alerts only after basics are stable.

Tip

Wireframe first. Building automation without a simple diagram leads to rework and brittle flows.

Step 16 — 📤 Apply and reach out beyond the portal

Apply with your tailored resume and a short cover note. Then contact three people: the recruiter or hiring manager, someone already in the role, and the role’s leader. Use multi‑channel outreach to avoid getting buried.

Email — Hiring manager
Subject: [Personalized hook for [Name]]

Hi [Name],

I saw [Company]’s opening for [Role] and just applied. Sharing my resume directly as my background in [Top 2–3 strengths] maps closely to [Team/Goal]. Happy to share examples of [Result/Metric]. Would a quick call be useful?

Thanks,
[Your Name]
[LinkedIn] • [Portfolio/Loom]
Email — Short punchy pitch
Subject: Quick question
Hi [Name], I found you when looking for [role/team] at [Company]. I use AI to surface relevant openings, tailor resumes to your JD, and reach the right contact. If my background in [X,Y] could help [Team Goal], worth a brief call?

Thanks,
[Your Name]
DM — Informational interview
I'd be very interested to get your expert opinion on this industry and where it's going, could you spare some time?
Email — Culture insight
Subject: [Personalized hook for [Name]]

Hi [Name],

See that you’ve been on the [Team] at [Company] since [Year]. I’m exploring opportunities on the team and wondered if you’d share what it’s been like and the culture.

Thanks in advance,
[Your Name]
Tip

LinkedIn DMs after applying get crowded. Use email plus one other channel (LinkedIn/Twitter). If asked for an application number you don’t have, email the recruiting/careers alias politely for help.

Step 17 — 🎥 Add optional proof links (no attachments)

Link to a short Loom introducing your background and motivation, a portfolio, or a case study doc. Keep links near the header or at the end; avoid large attachments.

Tip

Attachments add friction; links get clicked. If you record a Loom walkthrough of your profile, scroll the page so it doesn’t look static.

Step 18 — 🧩 If you’re a fresher or changing careers

Lead with projects, internships, and measurable wins from school or volunteer work. Emphasize time management, collaboration, resilience, and communication. If you’ve handled invoices/AR or strong internships, include them even if not required.

For support/health roles, highlight HIPAA, medical terminology, accuracy, and Microsoft Office/Excel. For tech/CX roles, include Zendesk/Intercom, basic SQL/JSON, and API familiarity if you have them.

Tip

Talk to practitioners to calibrate your bullets. Build role‑appropriate mini‑projects: SOC → logs/phishing labs; GRC → risk registers/control maps.

Step 19 — 🛡️ Cyber path (optional): 30‑day test and evidence

Unsure between SOC and GRC? Run a 30‑day split test: 15 days each. Read 5 SOC and 5 GRC JDs, learn the language, do a small project in each, and write a short summary. Pick the path where you can build explainable evidence fastest.

Template — 30‑day reflection
- Which work made me more curious?
- Which could I explain most clearly to a non‑expert?
- Which gave me stronger resume bullets and artifacts?
Tip

Don’t pick GRC because it seems easier—good GRC needs clear writing, evidence, stakeholder skills, and technical understanding.

Step 20 — 🧭 Interview alignment

Re‑read the JD and your tailored bullets before interviews. Prepare a crisp “Tell me about yourself” tied to the job’s top 3 priorities. Bring real examples of solving tough problems, staying calm, and going above/beyond.

Tip

Interviewers decide fast. Avoid rambling “volcano” answers. If you can’t talk confidently about your work, it’s hard to convince recruiters, peers, and managers.

Step 21 — 🚀 Optional: Upwork proposal system (for freelancers)

Re-use your resume tailoring engine to generate Upwork proposals and a workflow diagram. Use the prompts below.

Prompt — Upwork application (system + user)
System prompt: You are a helpful intelligent Upwork application writer.

User prompt: Your task is to take as input an Upwork job description and return as output a customized proposal.

Template example: Hi, I do [thing] all the time. I'm so confident I'm the right fit for you that I just created a workflow diagram plus a demo of your {{job description}} in no code. [Link]

About me: I'm a relevant job description that has done cool relevant things of note, other cool tie-ins. Very neat. Happy to do this for you anytime, just respond to this proposal else I don't get a chat window. Thank you.

Rules and formatting: Output in JSON format with keys for each section, use new line delimited bullet points, avoid emojis and flowery language, use first-person language.
Prompt — Google Doc proposal
You are a helpful intelligent proposal writer.
I'm an automation specialist applying to jobs on freelance platforms.
Your task is to take as input an Upwork job description and return as output JavaScript object notation for a customized proposal which I'll upload to Google Docs.

High performing proposals are typically templated as follows:
- Title of system
- Brief explanation of system
- Hi, as mentioned, I'm so confident I'm the right fit for this that I went ahead and created a proposal for you including a step-by-step of how I do it.
- I've done the below many times and working with specific part of their request is actually one of my favorite parts of automation.
- Here is how we'll build all of this stuff: left to right flow with arrows.
- A little bit about me: bullet points.

Rules:
- Write in a casual Spartan tone of voice.
- Don't use emojis or flowery language.
- If there's a name included somewhere in the Upwork job description, add it for personalization.
- Return step-by-step bullet points.
- Delimit each bullet point with a backslash and include a hyphen.
- Prefer not to mention social proof that includes money and numbers in about me bullet points.
- Use first-person language.
Prompt — Mermaid diagram
Your task is to take as input an Upwork job description and return as output a Mermaid diagram that I can visualize using a subsequent Mermaid live editor.

Example output:
graph TD
A[Receive email from Facebook lead ads] --> B[Add to CRM]
B --> C[Send customized SMS]

Rules:
- Only output flowcharts, no sequence diagrams, no Gantt charts.
- Do not output any accessory formatting information like backticks.
- Your first character should be 'g' (for graph TD).

Mistakes to avoid

🤖
Letting AI write everything

Template the structure yourself; have AI fill small, specific fields only.

🧱
Building automation without a plan

Wireframe your flow and test branches (PDF/DOCX/TXT) before scaling.

🔎
Ignoring the JD

Re-read the posting before interviews; tailor bullets to the top requirements.

📎
Using attachments

Share links (resume, portfolio, Loom). Attachments reduce views.

📜
Violating scraping TOS

Don’t auto-apply on Indeed. Scrape public data only for research/tailoring.

🧮
No metrics or outcomes

Vague bullets blend in. Quantify results with concrete numbers.

🗂️
Past-only resume

Aim bullets at the next role, not just what you did before.

🔐
Wrong file IDs & creds

Use correct Drive IDs; finish Google OAuth; store incomplete runs for recovery.

💬
Messaging only recruiters

Reach decision-makers too; use multi-channel to avoid inbox pileups.

Salary Estimate

$24–$30/hr
Park Aid customer support associate (source-reported)
$24–$30/hr + stipend + laptop
Park Aid overnight customer support associate (source-reported)
$20–$22/hr
Seresti Health enrollment specialist (source-reported)
$50–$60 per survey
Prolific survey earnings (source-reported, example-only)

Resources

Table of Contents

👇THE JOBHACKI ARSENAL

This guide is 1% of what members get

All 7 tools, 100+ grounded playbooks and 252 vetted tools, prompts and repos — on one membership.

Land your dream job. Start your dream business.

🚀
AI Auto Apply

Swipe real ATS jobs — we fill out and submit each application.

📊
Resume Match

Score your resume 0–100 against live roles before you apply.

📄
Resume Builder

Recruiter-tested one-page resume, auto-built from your LinkedIn.

🎯
Readiness Simulator

Paste a job link — get tested + your fastest study path.

🧰
Tool Directory

252 vetted tools, prompts, repos and GPTs across 86 categories.

💼
Job Directory

338,947+ live ATS jobs across 18,000+ company boards.

📚
Playbook Directory

100+ grounded, step-by-step income playbooks.

Join free today — All-Access is $7 for 7 days, then $27/month. Cancel anytime.

Learn More →
Log in / Dashboard