Creative problem solving with ai prompt course

Module 1: AI-Powered Problem Definition & Framing

1.1 Identifying Core Issues with AI Prompts

Identifying Core Issues with AI Prompts in creative problem solving with AI prompt courses means understanding why your AI prompt isn’t getting the result you want and pinpointing the specific part of the prompt causing the problem. It’s like diagnosing a car problem – you need to know if it’s the engine, the tires, or the steering wheel.

Here’s a breakdown:

The Goal: To get the AI to generate a specific, desirable output. If it’s not, the prompt is the problem.

The Process: Breaking down the prompt and analyzing its parts.

Core Issues Examples:

• Ambiguity/Vagueness: The prompt is too general.

  • Example: “Write a story about love.” (Too broad. Love can be romantic, familial, platonic, etc. The AI has too many options).
  • Solution: Be specific: “Write a short story about the love between a young baker and a busy architect in a bustling city.”

• Lack of Context: The AI doesn’t understand the background information needed to generate a relevant response.

  • Example: “Explain the impact of the bill.” (What bill? What country? What time period?).
  • Solution: Provide context: “Explain the impact of the American Health Care Act of 2017 on healthcare access in rural communities.”

• Conflicting Instructions: The prompt gives contradictory or incompatible directions.

  • Example: “Write a happy, sad story.” (The AI can struggle with such a direct contradiction).
  • Solution: Reframe the conflict: “Write a story about a bittersweet reunion between old friends, focusing on both the joy of reconnection and the sadness of realizing how much time has passed.”

• Unclear Desired Output Format: The prompt doesn’t specify the desired length, style, or tone of the output.

  • Example: “Describe Paris.” (A paragraph? An essay? A poem? Formal or informal?).
  • Solution: “Describe Paris in a short, vivid poem capturing its romantic atmosphere.”

• Misunderstanding of AI Capabilities: Asking the AI to do something it’s not capable of.

  • Example: “Predict tomorrow’s stock market.” (AI can analyze trends, but not perfectly predict the future).
  • Solution: Reframe the request: “Analyze recent stock market trends and identify potential factors that could influence tomorrow’s market performance.”

• Incorrect Terminology: Using jargon or terms that the AI may not understand or may interpret differently.

  • Example: “Optimize the paradigm shift.” (Vague and abstract; the AI may generate irrelevant responses).
  • Solution: “Explain how businesses can adapt to and benefit from the increasing adoption of remote work.”

Why It Matters: By identifying the core issues, you can refine your prompts and achieve better, more relevant, and more creative results from the AI. It turns prompt engineering from a guessing game into a systematic problem-solving process.

1.2 Reframing Challenges for AI Collaboration

1.3 AI-Assisted Root Cause Analysis

Module 2: Ideation & Solution Generation with AI

2.1 Brainstorming Techniques using AI Prompts

2.2 Generating Novel Solutions via AI

2.3 Evaluating Solution Feasibility with AI

Module 3: AI-Driven Decision Making & Prioritization

3.1 Using AI for Weighted Decision Matrices

3.2 AI-Based Risk Assessment for Solutions

3.3 Prioritizing Solutions Based on AI Insights

Module 4: Unlock Solutions to Personal and Professional Challenges

4.1 Applying AI to Personal Productivity & Goal Setting

4.2 Leveraging AI for Career Development & Problem Solving

4.3 AI-Enhanced Communication & Collaboration Skills