This is a submission for the Runner H "AI Agent Prompting" Challenge
What I Built
Being Student Preparing for highly competitive technical internships at top tech companies like Adobe, Google, Microsoft, Amazon, and others can be overwhelming. Aspiring candidates often struggle to understand the exact skill requirements, the nuances of the interview process, and how to build a structured, personalized study plan. This leads to wasted effort on irrelevant topics, missed application windows, and high stress levels.
To solve this, I built the Big Tech Intern Prep Agent, an autonomous AI workflow powered by Runner H. Starting from a single, detailed prompt, this agent researches a specific internship role at a leading tech company (e.g., Adobe Software Engineer Intern), analyzes the job requirements, studies common interview patterns, curates top study resources, and synthesizes all this into a personalized weekly study plan. It works like a smart, self-updating career coach and study planner, streamlining the entire prep journey for roles across companies.
Demo
Prompting Runner H with a detailed goal to generate a personalized study plan for a big tech software engineering internship
Runner H analyzing the official job description to extract required skills and responsibilities.
The final output is a comprehensive study plan in PDF format generated bt Runner H tailored to internship requirements, generated using the provided prompt and job description.
How I Used Runner H
I used Runner H to help me prepare for this.
Runner H’s autonomous capabilities allowed me to build this system without writing any code to interface with different websites. By giving it a single, structured prompt, the agent could:
Navigate to job of Adobe.
Parse job descriptions, required technologies (like Python, Java, C++, SDLC, etc.).
Scrape interview experiences from sites like GeeksforGeeks and Glassdoor.
Curate targeted learning paths from platforms like LeetCode, Coursera, and YouTube.
Generate a custom week-by-week study plan aligned with my goals, skill level, and schedule.
This process works not only for Adobe, but can easily be adapted for any big tech internship by simply updating the job URL and current skill level in the prompt.
Here's the exact prompt I used and how Runner H leveraged its capabilities:
Objective: Generate a highly targeted, comprehensive, and actionable study plan to maximize my chances of securing the Adobe 2025 Intern - Software Engineer (Job ID: R147746) position.
Phase 1: Deep Job Description & Company Research (Autonomous Observation & Information Gathering)
Analyze Official Job Description: Navigate directly to the provided job URL:
https://careers.adobe.com/us/en/job/R147746/2025-Intern-Software-Engineer.
- Thoroughly read and extract all required qualifications, preferred skills, core responsibilities, and technologies mentioned (e.g., Java, C++, JavaScript, Python, familiarity with SDLC, web/mobile app development).
- Note down any specific soft skills or cultural aspects emphasized by Adobe (e.g., collaboration, communication, problem-solving, versatility, adaptability).
Adobe Interview Process Research: Research typical interview processes for Software Engineer interns at Adobe. Look for information on online assessments, technical screens, coding rounds, system design (if applicable for interns), and behavioral interviews. Identify common question types and difficulty levels. Prioritize insights from recent (2024-2025) interview experiences on platforms like Glassdoor, LeetCode discussion forums, GeeksforGeeks, and similar career blogs.
Understand Adobe's Product Areas: Briefly research the Creative Cloud, Document Cloud, and Experience Cloud to understand the scope of work an intern might engage in, looking for general technology trends within these areas.
Phase 2: Skill Gap Analysis & Resource Identification (Intelligent Filtering & Prioritization)Current Skill Assessment: My current technical background is: [YOUR CURRENT PROGRAMMING LANGUAGES, DATA STRUCTURES/ALGORITHMS KNOWLEDGE, RELEVANT COURSEWORK, PROJECT EXPERIENCE, AND ANY SPECIFIC TECHNOLOGIES YOU ARE FAMILIAR WITH HERE. e.g., 'Intermediate Python, basic Java, familiar with fundamental data structures like arrays and linked lists, completed an intro to CS course, some experience with React/web development'].
Identify Critical Gaps: Based on the detailed requirements from Phase 1 and my current skills, identify the most critical technical and soft skill gaps I need to address for this specific Adobe role.
Curate Top Resources: For each identified skill gap or core requirement, find highly-rated and relevant online learning resources and practice platforms. Prioritize comprehensive and widely recognized resources.
Core Languages (Java, C++, JavaScript, Python): Find resources for strengthening proficiency in the languages mentioned in the job description that align with my current skills.
Data Structures & Algorithms (DSA): Identify structured courses and problem sets on platforms like LeetCode (focus on Easy/Medium Adobe-tagged problems if available), HackerRank, GeeksforGeeks.
Object-Oriented Programming (OOP): Find tutorials/courses specifically on OOP principles in the relevant language(s).
- Software Development Lifecycle (SDLC): Identify resources explaining modern SDLC practices, agile methodologies, testing, and deployment basics for web/mobile apps.
System Design (Basic): Find beginner-friendly introductions to system design concepts, tailored for interns/junior engineers.
Behavioral & Communication: Identify resources for common behavioral interview questions, resume/project discussion tips, and general communication strategies.
Optional (Adobe-specific): If relevant, find introductory resources on Adobe's specific technologies (e.g., Creative Cloud APIs, general cloud concepts, big data basics if hinted at).
Phase 3: Personalized Weekly Study Plan Generation (Structured Output & Time Allocation)
Generate a structured weekly study plan for a duration of [YOUR DESIRED PREPARATION TIMELINE, e.g., '10 weeks' or '3 months']. If no timeline is specified, assume a balanced 12-week preparation.
Allocate Study Hours: Assume a daily study commitment of [YOUR SPECIFIED DAILY HOURS, e.g., '2-3 hours on weekdays, 4 hours on weekends'].
For each week, define:
- Key Topics to Master: (e.g., "Week 1: Arrays, Strings, Basic OOP in Python"). Recommended Learning Path: Specific resource links from Phase 2 to use for that week's topics.
Practice Goals: Concrete coding problems to solve, behavioral questions to ponder, or concepts to review (e.g., "Solve 7 LeetCode Easy/Medium problems on Arrays," "Practice explaining a recent project using STAR method").
Mini-Project Ideas (Optional): Suggest 1-2 small project ideas that reinforce weekly learning or align with Adobe's product areas (e.g., a simple web app with a basic backend, a small image processing script).
- Integrate Regular Review: Include dedicated slots for spaced repetition, reviewing previously learned material, and solving mixed problem sets.
Phase 4: Interview Simulation & Application Strategy (Actionable Preparation & Final Polish)
Mock Interview Preparation: Outline a strategy for conducting mock interviews (peer-to-peer or self-simulated). Suggest how to articulate technical thought processes clearly and concisely.
Resume/Project Discussion Tips: Provide advice on how to effectively discuss past projects and experiences during interviews, relating them to Adobe's values and the job description.
Behavioral Question Bank: Generate a small list of common behavioral questions for Adobe or general tech internships.
Application & Networking Guidance: Suggest steps for tailoring the resume/cover letter, and briefly mention looking for Adobe recruiters/engineers on LinkedIn for informational interviews (if time permits).
Phase 5: Output & Presentation (Clear & Actionable Report)Present the entire study plan as a clear, well-formatted document (e.g., markdown or structured text output).
Include an initial summary of the Adobe job requirements and interview insights.
Ensure all resource links are clickable and organized by topic.
Conclude with actionable advice on tracking progress, maintaining motivation, and performing final interview preparations.
Goal: Deliver a self-contained, easy-to-follow roadmap that guides me from my current skill level to being well-prepared for the Adobe Software Engineer Intern role.
Use Case & Impact
The Intern Prep Agent has significant real-world applications and impact for aspiring software engineers:
Personalized & Targeted Preparation: Instead of generic study plans, this agent provides a roadmap directly tailored to the Software Engineer Intern role's specific requirements and the user's current skill set. This drastically improves study efficiency.
Time-Saving & Overwhelm Reduction: Manually researching job descriptions, interview processes, and finding relevant resources can take days, if not weeks. This agent automates that entire initial, tedious phase, allowing candidates to jump straight into focused studying. It reduces the common feeling of being overwhelmed by the sheer volume of information.
Increased Confidence & Effectiveness: By providing a clear, week-by-week plan with curated resources, the agent instills confidence and ensures a structured approach to preparation, leading to more effective learning and better interview performance.
Accessibility: It democratizes access to high-quality, personalized career preparation for competitive roles, benefiting students and career changers worldwide.
This solution truly exemplifies how Runner H can act as an intelligent, autonomous assistant, transforming a complex and time-consuming personal goal into an organized, achievable project.
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