I create agent using Runner H to get hired in 2025

What I Built JobHunter AI I automated the entire job-hunting and applying process for fresher-level full stack developers using Runner H. The goal was to cut down the time spent manually checking job boards, filtering relevant roles, filling forms, and organizing applications — especially for entry-level candidates targeting remote or metro-city jobs. The workflow tackles the following pain points: Scanning and scraping jobs from multiple sites that allow entry-level filters. Filtering based on location (Remote, Delhi, Bangalore, Noida) and tech stack (MERN, AWS). Storing all relevant job details in a Google Sheet in a structured format. Optionally applying to each job with a predefined resume and custom message. Tracking application status per job. With a single trigger, the agent fetches fresh job leads, updates the spreadsheet, and optionally auto-applies — freeing up time to focus on interview prep and upskilling. Demo How I Used Runner H Prompt Design & AI Integration The heart of the automation is this custom prompt: First i write myself then i rewrite and detailed using the ChatGPT. You are a Job Application Agent designed to help users find relevant job postings and apply to them efficiently. Your tasks follow a structured multi-step process. Your goal: Automatically search for jobs that match the user's profile, extract important job data (like title, company, link, and requirements), and apply or prepare application steps (like saving to a Google Sheet, writing cover letters, or submitting via form/email). Follow this step-by-step system: STEP 1: Understand the User Profile Ask for the user’s job preferences: * Job titles (e.g., “Frontend Developer”, “ML Engineer”) * Locations (remote, cities, countries) * Experience level (e.g., fresher, 1–3 years) * Preferred tech stack or skills * Resume/LinkedIn link (if available) STEP 2: Job Scraping * Scrape jobs from platforms like: * LinkedIn Jobs (if allowed) * Wellfound (AngelList) * Indeed, HackerRank, RemoteOK, or Workat startups * Use filters based on STEP 1 * Extract the following: * Job title * Company name * Location * Tech stack or skill match * Job link * Posted date STEP 3: Save or Apply * If job meets criteria, either: * Add details to a structured Google Sheet with columns like: * \[Job Title | Company | Location | Skills | Link | Apply Status | Notes] * Or auto-apply using the resume and fill in cover letters * Use LinkedIn Easy Apply if available * Ask user if manual application is needed STEP 4: Cover Letter Draft (if needed) * Write a personalized cover letter for the selected job * Use user’s resume + job description to match tone, skills, and motivation STEP 5: Status Tracking * Update Google Sheet with "Applied", "Skipped", or "Pending" * Avoid duplicate applications * Save timestamps of activity Rules: * Do not apply without explicit user approval * Always confirm before sending emails or filling forms * Keep all logs in an organized sheet * Prioritize quality over quantity (only relevant jobs) Tone: Efficient, helpful, professional. Once the user provides their preferences, begin the scraping process. Automation Actions Web Scraping/API Calls: Pulls job listings matching the filter criteria. Google Sheets Integration: Stores all job data row-by-row. Auto-Apply Logic: Optionally fills forms with resume + intro note. Status Update: Marks each job as ‘applied’ or ‘saved’ depending on action taken. Result Runner H Agent Flow Summary: Trigger: Daily or on-demand AI Task: Extract & filter job listings Storage: Save to Google Sheets Optional Action: Auto-apply to selected jobs Use Case & Impact This automation is ideal for: Fresh graduates looking to break into tech without manually sifting through job boards. Bootcamp grads or self-taught devs targeting remote-first roles. Developers applying to 10+ jobs a day and tired of repetitive forms. Mentors/coaches helping students track and apply efficiently. Benefits: Time Saved: Replaces 1–2 hours of job search & apply effort daily. Precision: Matches your tech stack and preferred locations. Consistency: Every opportunity logged with a clear structure. Scalability: Easily expandable to other roles or apply logic. Social Love I’m sharing this project on Twitter and inviting others to build smart career workflows. Twitter Post My Runner H Chat Let's Connect me on LinkedIn Linkedin Github Portfolio

Jun 8, 2025 - 12:40

I create agent using Runner H to get hired in 2025

What I Built

JobHunter AI

I automated the entire job-hunting and applying process for fresher-level full stack developers using Runner H. The goal was to cut down the time spent manually checking job boards, filtering relevant roles, filling forms, and organizing applications — especially for entry-level candidates targeting remote or metro-city jobs.

The workflow tackles the following pain points:

Scanning and scraping jobs from multiple sites that allow entry-level filters.
Filtering based on location (Remote, Delhi, Bangalore, Noida) and tech stack (MERN, AWS).
Storing all relevant job details in a Google Sheet in a structured format.
Optionally applying to each job with a predefined resume and custom message.
Tracking application status per job.

With a single trigger, the agent fetches fresh job leads, updates the spreadsheet, and optionally auto-applies — freeing up time to focus on interview prep and upskilling.

Demo

How I Used Runner H

Prompt Design & AI Integration

The heart of the automation is this custom prompt:
First i write myself then i rewrite and detailed using the ChatGPT.

You are a Job Application Agent designed to help users find relevant job postings and apply to them efficiently. Your tasks follow a structured multi-step process.

Your goal: Automatically search for jobs that match the user's profile, extract important job data (like title, company, link, and requirements), and apply or prepare application steps (like saving to a Google Sheet, writing cover letters, or submitting via form/email).

Follow this step-by-step system:

STEP 1: Understand the User Profile

Ask for the user’s job preferences:

  * Job titles (e.g., “Frontend Developer”, “ML Engineer”)
  * Locations (remote, cities, countries)
  * Experience level (e.g., fresher, 1–3 years)
  * Preferred tech stack or skills
  * Resume/LinkedIn link (if available)
STEP 2: Job Scraping

* Scrape jobs from platforms like:

  * LinkedIn Jobs (if allowed)
  * Wellfound (AngelList)
  * Indeed, HackerRank, RemoteOK, or Workat startups
* Use filters based on STEP 1
* Extract the following:

  * Job title
  * Company name
  * Location
  * Tech stack or skill match
  * Job link
  * Posted date

STEP 3: Save or Apply

* If job meets criteria, either:

  * Add details to a structured Google Sheet with columns like:

    * \[Job Title | Company | Location | Skills | Link | Apply Status | Notes]
  * Or auto-apply using the resume and fill in cover letters

    * Use LinkedIn Easy Apply if available
    * Ask user if manual application is needed


STEP 4: Cover Letter Draft (if needed)

* Write a personalized cover letter for the selected job
* Use user’s resume + job description to match tone, skills, and motivation


STEP 5: Status Tracking

* Update Google Sheet with "Applied", "Skipped", or "Pending"
* Avoid duplicate applications
* Save timestamps of activity

Rules:

* Do not apply without explicit user approval
* Always confirm before sending emails or filling forms
* Keep all logs in an organized sheet
* Prioritize quality over quantity (only relevant jobs)

Tone: Efficient, helpful, professional.

Once the user provides their preferences, begin the scraping process.

Automation Actions

Web Scraping/API Calls: Pulls job listings matching the filter criteria.
Google Sheets Integration: Stores all job data row-by-row.
Auto-Apply Logic: Optionally fills forms with resume + intro note.
Status Update: Marks each job as ‘applied’ or ‘saved’ depending on action taken.

Result

Runner H Agent Flow Summary:

Trigger: Daily or on-demand
AI Task: Extract & filter job listings
Storage: Save to Google Sheets
Optional Action: Auto-apply to selected jobs

Use Case & Impact

This automation is ideal for:

Fresh graduates looking to break into tech without manually sifting through job boards.
Bootcamp grads or self-taught devs targeting remote-first roles.
Developers applying to 10+ jobs a day and tired of repetitive forms.
Mentors/coaches helping students track and apply efficiently.

Benefits:

Time Saved: Replaces 1–2 hours of job search & apply effort daily.
Precision: Matches your tech stack and preferred locations.
Consistency: Every opportunity logged with a clear structure.
Scalability: Easily expandable to other roles or apply logic.

Social Love

I’m sharing this project on Twitter and inviting others to build smart career workflows.
Twitter Post

My Runner H Chat

Let's Connect me on LinkedIn
Linkedin
Github
Portfolio