Strategic Thinking Weekly #1: The Problem with Just Ask AI

Field Note

The Problem with "Just Ask AI"

Last month, I watched a company spend over $2,000 on ChatGPT Plus accounts because their team "needed better AI." Same prompts, same inconsistent results, now with a bigger bill.

The problem wasn't the AI. It was the missing framework.

Or consider this: when you're explaining complex compliance services to clients who speak Spanish as their first language, you can't rely on "just prompt better." You need systematic intelligence that works the same way every time, regardless of which AI tool you're using.

That's the constraint most professionals face now: AI is everywhere, but frameworks for using it systematically are rare. The companies that figure this out first will have an unfair advantage that lasts until their competitors catch up.

Which might be 12-18 months. Maybe less.

Case Slice Teardown

From Inconsistent to "Way Easier" in 6 Weeks

Role: Bilingual sales representative

Situation: Explaining complex compliance services to Spanish-speaking clients. Technical complexity + language considerations created inconsistent client conversations.

Constraint: Needed systematic approach that worked across different client scenarios without relying on memorization.

Intervention: Applied custom framework methodology to structure client explanations.

Outcome: Client conversations became "way easier" with increased confidence. Sustained daily usage for 6 weeks. Would recommend to other bilingual sales professionals.

What's notable here: This wasn't about learning more product knowledge or improving language skills. It was about having a systematic way to approach each conversation. The framework made the constraint (technical complexity + bilingual communication) into a solvable pattern rather than a daily struggle.

Judgment Gate: 3 Tests Before You Build

1. Is the problem defined as a decision?
"Make better presentations" fails. "Choose which 3 data points matter most" passes.

2. Is a boundary named explicitly?
"Improve communication" fails. "Explain in under 2 minutes to non-technical clients" passes.

3. Is the primary metric's penalty clear?
"Increase engagement" fails. "Reduce time-to-close (penalty: extended sales cycles cost $X per week)" passes.

These aren't steps in a process. They're criteria you use to judge whether a framework will actually work before you waste time building it. Most AI outputs fail all three tests, which is why they feel generic and don't transfer across situations.

3-Minute Micro-Win

Try this right now with something you're working on

Take your current AI output (anything you're using for work: email template, presentation outline, process documentation)

Rewrite the core problem as a decision question
Before: "Improve our onboarding"
After: "Should we prioritize product training or relationship building in week 1?"

Name one boundary
"Must complete in 5 business days with zero IT support needed"

Pick your primary metric and state what it penalizes
"Time to first productive output (penalty: each extra week delays revenue by $X)"

Notice the difference? The "after" version can actually be evaluated. The "before" version just generates more generic advice.

STRATEGIC THINKING WEEKLY

Framework Builder Edition

The Problem with "Just Ask AI"

From Inconsistent to "Way Easier" in 6 Weeks

3-Minute Micro-Win

Learn the Systematic Thinking Methodology