PROMPT This AI Challenge
"The Analyst’s View of AI: Judgment, Costs, and Realā€‘World Use" featuring Bruce Daley
Every episode of the PROMPT This podcast includes an AI Challenge for the audience. Follow the instructions below to complete this episode's challenge.
Most people treat AI like a vending machine.
- They type a question.
- They get an answer.
- Then they decide whether AI is “good” or “bad.”
That is the wrong test. The real variable is not the AI model. It is the prompt you put in.
Prompt engineering is quickly becoming a professional skill. The people who learn to direct AI well will have a structural advantage over the people who do not.
This challenge lets you feel that difference in less than ten minutes.
The Challenge
Take one simple business question.
For example:
"Explain the CRM market.”
Now run the same question through AI three different ways.
1. Basic Prompt
Start with the simplest version.
Prompt:
Explain the CRM market.
This is how most people interact with AI today.
It produces a generic answer. Usually accurate. Often shallow.
2. Structured Prompt
Now add some basic structure.
Prompt:
Explain the CRM market.
Tone: analytical
Audience: business executives
Format: bullet points
Include: market size, major vendors, vendor tradeoffs, and current trends
Limit: 200 words
Notice what changed. You did not add more information. You added constraints and clarity. This is where the output starts to become useful.
3. Expert Prompt
Now run an expert-level prompt.
Prompt:
Act as a senior technology industry analyst.
Explain the CRM market to a private equity partner evaluating investments in enterprise software.
Include:
- Market size and growth rate
- Major vendor segments (enterprise, midmarket, SMB)
- Competitive positioning of Salesforce, Microsoft, HubSpot, and emerging players
- Key trends affecting the next five years
Output requirements:
- 5 bullet insights
- 1 short paragraph on risks
- 1 short paragraph on investment opportunities
This version introduces role, audience, boundaries, and output specifications.
Now the AI behaves like a domain expert delivering a structured briefing.
What to Observe
After running the three prompts, compare the answers.
Ask yourself three questions.
1. How much did the quality improve?
In most cases the expert prompt produces an answer that is dramatically more useful.
2. Which prompt elements mattered most?
Typical drivers include:
-
Role definition
-
Audience clarity
-
Output format
-
Specific constraints
3. What elements would you reuse?
Many professionals eventually build reusable patterns such as:
Role + Audience + Task + Format
Once you internalize that structure, every AI interaction improves.
Why This Matters
The right prompt can produce an enormous amount of high-quality work.
That is not theoretical. It is operational.
Engineers use prompts to generate code.
Marketers use prompts to analyze campaigns.
Manufacturing teams use prompts to summarize technical documentation.
Consultants use prompts to create structured client briefings.
The professionals who learn to direct AI effectively will operate at a different level of productivity.
This challenge demonstrates that gap in about ten minutes.
Final Thought
AI capability is not evenly distributed.
The difference often comes down to how clearly you ask the machine to work.
That is why prompt engineering is emerging as a real professional skill. And why mastering it now will compound over time.
