Podcast Summary: Everyday AI Podcast – "Creative Frameworks for Problem-Solving with Generative AI"

Date: December 17, 2025
Host: Jordan Wilson
Guest: Leslie Grande, Lead Executive in Residence, Executive Education, University of Washington

Episode Overview

This episode dives into how professionals can leverage generative AI—not just for efficiency, but as a true thought partner to unlock creative problem-solving. Jordan Wilson is joined by Leslie Grande, an experienced innovation leader and educator, who shares practical frameworks and best practices for using AI to augment—not replace—human agency and creativity in the workplace.

Main Topics & Key Insights

The Pitfall of Speed Over Depth

• Mindless Usage of AI Models

  • Most users turn to large language models (LLMs) like ChatGPT or Claude for quick, copy-paste answers, often prioritizing speed over meaningful results or deeper understanding.
  • Quote:
    “You're probably just looking for an output... That's probably not the best way to use it.” – Jordan Wilson (00:25)

• AI as Thought Partner, Not Answer Machine

  • The real value comes from engaging with AI to augment your own thinking, not to outsource it entirely.
  • Many fail to question the output or understand the decision process behind it.

Leslie Grande’s Journey & “Aha” Moments with LLMs

• Background

  • Former film industry professional, later transitioned to product management at tech giants; wrote the book "Creative Velocity".
  • Saw the need to foster creative agency and confidence among teams, using AI as a supporting tool.

• Key Learning: Speed Doesn’t Equal Smart

  • Story (03:35): Created an exercise for her book; when posed to an LLM, it skipped 3 of 15 key facts and produced an incorrect answer.

  • Quote:
    “The fastest answer wasn't the right answer... Speed triumphs over smart and comprehensive.” – Leslie Grande (04:23)

  • This highlighted the importance of questioning AI outputs and not delegating critical/creative-thinking tasks to AI without scrutiny.

Maintaining Human Agency and Critical Thinking

• Problems with Prompt Engineering

  • Relying solely on prompt engineering (Q&A cycles) can cause users to let AI do the thinking—outsourcing one’s own mental agency.
  • Push for more open-ended, exploratory prompts instead of narrow queries.

• Framework: Generic Parts Technique

  • Break down a problem into generic, functional components to reveal underlying issues and spark more creative solutions.
  • Example (09:04): Using the authentication pain point at hotels/Airbnbs to rethink the root problem, leading to fresh solutions.

• Context Engineering

  • The evolution from "prompt engineering" to "context engineering" involves supplying richer, more personalized or situational context to elicit more relevant and useful responses.
  • Personalization and data context are becoming central, but so is retaining human oversight on output quality.

The Human-in-the-Loop: Divergent vs. Convergent Thinking

• AI Converges, Humans Diverge

  • AI tends to converge on answers algorithmically; humans bring in emotions, context, and intuition—qualities LLMs lack.
  • Quote (12:16):
    "What we value and what meaning we ascribe to things aren't innately in the answer you get from AI... So being able to challenge the value of the answer as it relates to meaning and purpose is really a critical component." – Leslie Grande

• Best Practices for Collaboration with LLMs

  • Use multiple models to compare outputs and surface divergent thinking.
  • Try both “known” (customized/memorized) and “anonymous” (fresh start, no chat history) approaches to check for bias and broaden the solution space.
  • Feed the output from one model into another to critique and iterate.

Creative Problem-Solving Frameworks for AI Collaboration

1. Generic Parts Technique (GPT)

• Purpose: Breaks problems into their most basic functional elements to overcome “functional fixedness.”
• Practice: Available as a custom GPT Leslie created within ChatGPT (16:15).
• Quote:
  “You can build a GPT to teach somebody one of these frameworks.” – Leslie Grande (16:15)

2. SCAMPER

• Origin: Developed by the advertising agency BBDO.
• Acronym: Substitute, Combine, Adapt, Modify, Put to another use, Eliminate, Reverse.
• Use Case: Forces creative consideration of alternative approaches to any step of a process or problem.
• Example (17:15): Curbside pickup in retail as a product of “combine” and “reverse” moves.

Unlocking Creative Confidence with AI

• Combating Cognitive Bias

  • LLMs can help break natural tendencies or biases (from expertise, personal experience) by serving up psychologically-distanced perspectives.
  • Example (21:16): Borrowing from nature (swarming insects) to innovate in drone warfare.

• Looking Outside the Domain

  • LLMs can assist by suggesting analogous solutions from other industries or problem domains.

Personal Reflection: Technology in Retrospect

• Earlier Career Application
  • Having today’s LLMs would have provided Leslie with “neutral third-party” input, easing resistance in change-averse environments.
  • AI-provided ideas could serve as a conversation starter, reducing the perception of personal criticism and stimulating broader team thinking.
  • Quote (23:33):
    “It might have been easier if this neutral third party with psychological distance known as ChatGPT or Claude, would be the person in the room saying it instead of me.”

Final Takeaways & Advice

• Use Frameworks to Retain Creative Agency

  • Don’t default to efficiency at the expense of creativity or meaning.
  • Building confidence with these frameworks gives you “agency over the output” to ensure relevance, meaning, and value before implementation.
  • Quote (25:53):
    “We're tempted to outsource creativity in the interest of efficiency and speed. And I think it's exactly the opposite that you need to do.” – Leslie Grande

• Challenge and Test AI Suggestions

  • Always challenge and refine AI outputs, applying frameworks to enhance them before acting on their suggestions.

Notable Quotes & Timestamps

• "Speed triumphs over smart and comprehensive... That was the biggest aha moment for me." – Leslie Grande (04:23)
• "Being able to challenge the value of the answer as it relates to meaning and purpose is really a critical component." – Leslie Grande (12:16)
• "Using multiple tools I think is super critical... I even like to take the answer from one tool and put it in the other tool and I like to see how the other tool responds to what it saw as the answer I provided it." – Leslie Grande (15:37)
• "We're tempted to outsource creativity in the interest of efficiency and speed. And I think it's exactly the opposite that you need to do." – Leslie Grande (25:53)

Timestamps for Key Segments

• 00:25: The problem with using LLMs for speed over deliberation
• 03:35–05:56: Leslie Grande’s first “aha” moment and the limits of quick AI answers
• 06:50–10:16: The importance of open-ended, creative prompts and the generic parts technique
• 12:16–14:19: Human in the loop: divergent vs. convergent thinking and meaning
• 15:54–17:45: Using multiple models; explanation of SCAMPER framework
• 20:12–23:33: Overcoming cognitive bias & analogical reasoning with LLMs
• 23:33–25:53: How LLMs could have helped in earlier product/strategy roles
• 25:53–end: Final advice on retaining creative agency with AI frameworks

Conclusion

This episode offers a comprehensive guide on using AI for creative problem-solving—emphasizing depth over speed, the integration of structured frameworks (like Generic Parts Technique and SCAMPER), and the essential need for human agency and critical oversight. By maintaining creative confidence and challenging outputs, listeners can ensure that AI serves as a meaningful collaborator in problem-solving and strategy, rather than just an efficiency tool.