Prompt Engineering Assignment
This repository documents my work for the AI/ML Prompt Engineering Lab for ITAI.1370.501.2026SP. The purpose of this lab is to explore how iterative prompt engineering can be used to improve the quality, relevance, and usefulness of AI-generated outputs. Using multiple Large Language Models (LLMs), I will generate and refine a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis for a company aligned with my desired field of work.
Rather than focusing on a single prompt, this lab emphasizes experimentation, comparison, and refinement. Each iteration builds on the last, demonstrating how small changes in prompt structure, constraints, and context can significantly affect outcomes. The final deliverable connects the SWOT analysis directly to an interview scenario within my field of study.
Through this project, I aim to:
- Practice iterative prompt engineering in a real-world business context
- Compare outputs from multiple accessible LLMs
- Evaluate AI responses for clarity, accuracy, and relevance
- Apply my field of study to an interview-ready SWOT analysis
- Document and present my workflow using GitHub
- Repository created
- Company selection - Cisco Systems
- LLM selection - Copilot and paid ChatGPT
- Files uploaded
- Project Complete
This README will be updated once a company has been selected and analysis work begins.
AI-ML-Prompt-Engineering-Lab/
├── README.md # complete
├── Prompt_Revisions.docx # Documented prompts, outputs, and comparisons
└── swot_analysis.pdf # Final polished SWOT analysis
Final prompt
Generate a SWOT analysis for Cisco Systems, a tech company based in california, from the perspective of a technical program manager candidate preparing for an interview. In a concise, bullet-point format, highlight how program and project management impacts the company's Strengths, Weaknesses, Opportunities, and Threats. Use a professional tone.
All AI outputs used in this project will be clearly labeled by model and iteration. Any final deliverables may be lightly edited for clarity, formatting, or accuracy while preserving the intent of the AI-generated content.