Posts
Using a Priority Matrix: Assessing Research Risk and Problem Clarity for Your Product Design Projects
My Venn Diagram of Specialities: Academic Rigor Meets Startup Speed
The Right People, The Right Research: Field Notes from a Decade of Building High-Signal Participant Programs
Documentation as a Trust-Building Tool: A Strategic Approach to Change Management & Program Adoption
I Built a Website in 21 Days: Documenting my Design, Accessibility, and Programming Language Journey
When Autoship Fails to be Automatic: Task Analysis Case Study
This Matrix is Real: Using Win Expectancy Matrix Calculations During Live Baseball Games
If A Baseball Analytics Tree Is Described In A Forest, Can Anyone See It?
What Are Layoffs?An Organizational Behavior Perspective
How to Train GenAI to Work as Your Personal Research Assistant
Mid-Season Closing Pitcher Reevaluation Strategy: Help From My Gen AI Assistant
Selecting Which Players When: GenAI Prompting for Fantasy Baseball Draft Strategy
Figure 1: ChatGPT Dall-E 3 generated image, ostensibly depicting our draft strategy+ - this is a footnote you’ll be sorry to miss
TL;DR Getting information inputs, or “prompts”, wrong could mean your GenAI assistant helped you develop a useless strategy. In fantasy baseball, it’s not the end of the world. But it might be when wrongfully applied to a crucial product development for your business, for example.
This post is an expanded addendum to my previous one, on using Generative AI for developing a fantasy baseball draft strategy (I’m using ChatGPT). I’ll give away the ending — regardless of utilizing GenAI or not, this post is also a foil for how a draft strategy is only as good as your ability to draw upon your own previous research, in a live format++.