Why Prompting Harder Won't Fix Your AI Results

Описание: Most people blame the AI when output is mediocre. The real problem? They never gave it any context for who they are, how they work, or what done looks like.

In this episode of AI Calibration Weekly, Zack Glaser sits down with Ben Schorr, Drew Bloom, and Stephanie Everett to unpack why some people get extraordinary AI output — and most don't. The answer isn't smarter prompting. It's better onboarding.

What you'll learn:

Why giving your AI context is exactly like onboarding a new hire — and how to do it right
How to build context files (markdown docs, SOPs) that make AI output more consistent and on-brand
The difference between AI "skills," "memories," and "personalization" — and where your system's special sauce actually lives
Why iterating section by section beats single-shot prompting every time
How to use AI to audit, improve, and stress-test your own processes

About the panelists:

Ben Schorr is a Microsoft MVP and legal technology expert who has spent years building AI workflows. Drew Bloom brings a systems-level lens to AI adoption and implementation. Stephanie Everett is a law firm business strategist and host of the Lawyerist Podcast. Together, they advise law firms and legal teams on AI adoption that actually sticks.

Chapters:

00:00 Introduction — What Debbie's AI Does That Ours Can't
01:30 Why AI Needs Context: The New Hire Analogy
04:00 Building Context Files and Markdown Docs
06:00 Transferring Your AI Setup Between Tools
08:30 Skills vs. Memories: Where Your "Special Sauce" Lives
10:00 Training AI on Your IP — Is That a Risk?
11:00 Iterating Section by Section: Stephanie's Approach
13:30 Ask AI to Do What You Know It Can Do
15:00 Why Process-First Thinkers Win at AI
17:00 When to Give AI Some Leash
18:30 Using AI to Improve Your Own SOPs
20:30 Layering Audience Context: Client and Judge Profiles
22:30 Where to Find Ben, Drew, and Stephanie

Ready to assess your firm's AI readiness?

https://www.affinityconsulting.com/ai...

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