Personal Strategy: Using
AI to Architect My MBA
Faced with choosing my second-year MBA electives and the additional constraints imposed by my second degree, I decided to treat it like a strategic consulting project. I used a panel of six different AIs as expert thought partners, prompting them to deconstruct my career goals and design a curriculum that was intentionally future-proof and not just a random collection of interesting classes.
Project Overview
Role
Prompt Engineer
Duration
Summer 2025
Tools
Custom GPT & AI Panel, Perplexity, WEF 'Future of Jobs Report', BC Course Catalog
Skills
AI Prompt Engineering, Strategic Planning, Comparative Analysis
My Approach
My approach was to treat this personal decision like a professional consulting engagement. Instead of relying on a single source of truth, I used a panel of six different AIs (including models from Google, OpenAI, and Anthropic) as expert strategic thought partners.
I started by writing a single, detailed prompt that served as a strategic brief, outlining my background, skills, and the constraints of my dual-degree program. After running this through the panel, I synthesized the key insights from all six outputs to create a final "meta-prompt."
The goal of this second step was to have a final AI strategist analyze the collective intelligence of the panel and build a unified blueprint. To ground the process, I had the models validate their recommendations against the World Economic Forum's "Future of Jobs Report." Finally, to challenge any assumptions from that single source, I used Perplexity for an additional validation round against other trend reports, ensuring the final approach was rigorously researched.
The Outcome
The process worked. The AI's analysis bypassed generic advice and recommended several "capability stacks." The one I chose focused on the intersection of high-level finance and corporate strategy.
This led directly to my decision to enroll in advanced electives like Venture Capital, Corporate Valuation, and Mergers & Acquisitions. The result is a curriculum that feels intentional, cohesive, and directly aligned with my goal of becoming an empathetic, full-stack leader for the AI era.

The final output from the AI panel was this strategic blueprint. It's a detailed, 12-course curriculum built around a core "capability stack" called "The AI-Enabled Strategic Advisor." This became my definitive roadmap for my final year of electives.
Project Artifacts & Workflow
Step 1: The "Futurist" Prompt
The entire project began with a single, detailed prompt designed to elicit a strategic, forward-looking response.
Click to view the complete AI strategic prompt
Step 2: The AI Panel Analysis
I started by running a single, detailed prompt through a panel of six AIs to gather a diverse set of perspectives.






To synthesize these without bias, I exported and anonymized each conversation as "Model A," "Model B," and so on. I then fed all six outputs into Gemini 2.5 Pro (chosen for its high performance and the massive context window needed for this workflow) and tasked it with building the final, unified strategy.
Step 3: The Meta-Prompt SOP & Synthesis
The second step was the critical one. I didn't just ask the final AI to summarize; I engineered a detailed "meta-prompt" that acted as a formal Standard Operating Procedure (SOP). This prompt instructed the AI to act as a deterministic research director, with strict protocols for citing evidence, scoring the initial models, and producing a fully auditable analysis. To ensure the process was fully traceable, I specifically required the AI to structure its final output as a machine-readable JSON file, turning a series of conversations into a structured dataset.

The opening section of the meta-prompt established a strict persona and operating framework for the final AI analysis.
Click to view the complete meta-prompt SOP
Step 4: Final Validation & Red Teaming
The final step was to challenge the blueprint generated by the meta-prompt. While the process was grounded in the WEF report, I wanted to avoid relying on a single source of truth. I tasked Perplexity with a final deep research report, instructing it to interrogate our conclusions against other reputable forecasts and trend data. This ensured the final strategy was not just well-synthesized, but validated against a broader set of external evidence.
Executive Summary
Decision Recommendation: OPTIMIZE AI panel elective strategy within BC Carroll course constraints
Confidence Level: 4/5 - High confidence with validated course availability
Key Evidence: AI skills command 21 - 47% salary premiums [1] [2] [3], BC Carroll offers strong AI+Finance curriculum alignment
Strategic Modification: 2 course substitutions required, 94% optimization effectiveness achieved
