Almost let ChatGPT do my portfolio project for me. Glad I didn't.

Working on a dynamic pricing analysis for my BA portfolio - real CPG data, 30 stores, trying to model price elasticity scenarios in Excel.

Hit a wall when I had to actually use the elasticity coefficients (-0.4, -1.2, -0.8) to calculate demand changes. I understood the theory but froze when it came to application.

Typed into ChatGPT: "Can you just build the Excel workbook for me?"

Then remembered I literally told it earlier in the session "no solutions, I need to figure this out myself."

Took a break. Worked through it manually. And holy shit, the insights:

• Rural weekday customers (elasticity -0.4): 10% price increase = only 3 units lost. Loyal AF.
• Urban weekend customers (elasticity -1.2): 5% price decrease = 17 additional units. Super price-sensitive.

The formulas aren't the hard part. It's understanding what the numbers mean about actual customer behavior.

If I'd taken the shortcut, I'd have a pretty spreadsheet and zero understanding. When an interviewer asks "walk me through your approach," I'd have nothing.

Just a reminder to myself (and anyone building a portfolio): the struggle is literally the point. The messy middle is where the learning happens.

#AIinEducation #LearningDesign #Upskilling #FutureOfLearning #DynamicPricing #Analytics