Business leaders face the challenge of moving beyond AI dabbling to strategic mastery, where artificial intelligence becomes the operating system of their organization rather than just another technology overlay. The episode reveals that 90% of AI pilot projects fail due to lack of strategic alignment and proper data infrastructure. Companies like Moderna are already restructuring their entire organizations around the combined human and digital workforce concept, signaling a fundamental shift in how businesses must operate. The key insight is that AI without access to internal data is like hiring a new employee and blindfolding them - they can't contribute meaningfully to business intelligence. Successful organizations treat AI as the foundation of their operations, creating intelligent systems that provide real-time decision-making capabilities and competitive advantage.

Highlights

• Treat AI as your organization's operating system, not just a technology add-on
• Overcome data access fears to transform AI from helpful stranger to informed coworker
• Shift from generative AI dabbling to agentic AI with internal data integration
• Create closed-loop systems where AI leverages your unique business intelligence
• Implement daily practice and pilot projects with clear ROI measurements
• Restructure organizational thinking around combined human-digital resources
• Develop AI-first business models rather than overlaying AI on existing processes
• Commit to continuous learning and mastery rather than instant gratification

Important Concepts and Frameworks

• George Leonard's Mastery Framework - Understanding the journey through dabbling, hacking, obsessing, and mastery phases
• AI as New Employee Analogy - The importance of data access for AI effectiveness
• Intelligent Organizations - Companies where AI provides real-time intelligence at decision moments
• AI Native Mindset - Building businesses with AI as the foundational operating system
• Agentic vs Generative AI - The difference between AI that acts on data versus generates content
• Closed Loop Systems - AI implementations that leverage internal organizational data
• Digital Transformation Roadmap - Strategic approach to becoming an AI-first organization

Tools & Resources Mentioned

• OpenAI Atlas Browser - AI-integrated browser with commercial ecosystem - https://openai.com/
• Claude Code - AI coding capabilities within Anthropic's Claude - https://www.anthropic.com/product/claude
• ChatGPT - Generative AI platform for content creation - https://chat.openai.com/
• Google Gemini - AI assistant and content generation tool - https://gemini.google.com/
• Perplexity AI - AI-powered search and research platform - https://www.perplexity.ai/
• Airtable - Platform for organizing and accessing business data - https://www.airtable.com/
• PayPal - Payment processing for AI commercial ecosystems - https://www.paypal.com/

Calls to Action

1. Shift your mindset from viewing AI as technology overlay to organizational operating system
2. Conduct a data infrastructure audit to identify accessibility barriers for AI implementation
3. Start daily practice with agentic AI tools that can access and act on your business data
4. Create pilot projects with clear KPIs and ROI measurements rather than random experimentation
5. Restructure organizational thinking around combined human and digital workforce capabilities
6. Develop an AI-first business model rather than trying to retrofit AI onto existing processes
7. Commit to continuous learning and mastery journey rather than seeking instant gratification

Key Quotes

• "AI without data is like hiring a new employee and blindfolding them" — Mark Redgrave
• "We're in the dial-up stage of AI, not ready to replace airline pilots yet" — Marvin Dejean
• "AI must be in service of strategy, not strategy in service of AI" — Mark Redgrave
• "The companies that succeed will treat AI as their operating system" — Marvin Dejean
• "You better learn to love the plateau because you'll spend most time there" — Mike Richardson

Chapters
00:28 — Welcome and Recent AI Developments Overview
02:02 — OpenAI Atlas Browser and AI Ecosystem Strategy
03:20 — Moderna's Bold Organizational Restructuring Move
05:57 — Marvin Dejean's AI Journey Since 2012
12:18 — The Critical Role of Data in AI Implementation
18:17 — AI as New Employee: Data Access Analogy
21:49 — Overcoming Data Infrastructure Challenges
25:21 — Future AI Interface and Browser Integration
28:24 — Mastery Framework for AI Adoption Success
31:44 — Daily Practice and Commitment to Learning
33:54 — Strategic Alignment and Avoiding Instant Gratification
38:39 — Separating Wheat from Chaff in AI Implementation
41:29 — Practical Actions for Moving Beyond AI Dabbling
44:00 — AI as Organizational Operating System Mindset
48:08 — Closing Thoughts and AI Incubator Announcement

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Our Guest on this episode

Marvin Dejean
LinkedIn: https://www.linkedin.com/in/marvindejean/

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Meet the Crew

Mike Richardson – Agility, Peer Power & Collective Intelligence
Website: https://mikerichardson.live/
LinkedIn: https://www.linkedin.com/in/agilityexpertmikerichardson/

Ryan Niemann – Software CEO & Board Operator
Website: https://bob3.pro/
LinkedIn: https://www.linkedin.com/in/ryanniemann/

Mark Redgrave – Agility, People and Performance
Website: https://www.shift-transform.com/
LinkedIn: https://www.linkedin.com/in/mredgrave/

Tom Adams – Executive Coach, Advisor & Trail Blazer
Website: https://tomadams.com/
LinkedIn: https://www.linkedin.com/in/tomadamscoach/

Business leaders face overwhelming uncertainty about AI implementation, with executives privately admitting "I don't know what I'm doing" despite mandates from the top. The AI resistance stems from competing priorities, limited time, and the sheer volume of change overwhelming even experienced leaders. Rather than seeking confidence through knowing, successful leaders build confidence through curiosity and learning. The Matthew Effect shows that early AI adopters gain compounding advantages, while those who wait fall further behind. Key strategies include finding your "coalition of the willing" rather than convincing skeptics, treating AI as a service to existing strategy rather than the strategy itself, and embracing small experiments to build capabilities through commitment and courage.

Highlights
- Build confidence through curiosity rather than traditional knowing-based leadership
- Find your coalition of the willing instead of wasting energy on convincing skeptics
- Treat AI as service to strategy rather than making AI the strategy itself
- Early adopters gain compounding advantages through the Matthew Effect
- Create organizations that reward questions rather than demanding answers

Important Concepts and Frameworks
- Matthew Effect in AI — Early advantages compound for AI adopters while others fall behind
  - Link: https://medium.com/@geopertea/the-ai-matthew-effect-pay-to-play-intelligence-supercharges-inequality-128bb4a36430

- Navigating the Jagged Technology Frontier — BCG/Harvard study showing AI shifts performance one standard deviation
  - Link: https://www.hbs.edu/ris/Publication%20Files/24-013_d9b45b68-9e74-42d6-a1c6-c72fb70c7282.pdf

- Confidence Framework — Dan Sullivan's commitment-courage-capabilities-confidence cycle
  - Link: https://www.couragetoanswer.com/blog/blog-post-title-four-s9s8j

- Trust Triangle — Capability, consistency, and selflessness as foundations of trust
  - Link: https://www.linkedin.com/pulse/trust-triangle-framework-leadership-excellence-dr-nik-eberl-lj5ff/

- Coalition of the Willing — Organizational change driven by pulling rather than pushing

Tools & Resources Mentioned
- Claude 4.5 — AI assistant with new planning capabilities
- Codex — OpenAI's code generation system
- Wall Street Journal — Source for AI Matthew Effect article
- Fortune — Article on executive AI uncertainty by Heather Conklin

Calls to Action
1. Find 2-3 people in your organization to form a learning team around AI
2. Schedule 2 hours per week dedicated to AI experimentation and learning
3. Identify one small process where AI could create immediate value
4. Stop trying to convince skeptics and focus on your coalition of the willing
5. Commit to one AI experiment this week, regardless of outcome

Key Quotes
- "Your confidence now needs to come from curiosity" — Mark Redgrave
- "Create an organization that rewards questions, not answers" — Mark Redgrave
- "AI is in service of your strategy, not the strategy itself" — Mark Redgrave
- "Find your coalition of the willing and go hard" — Mark Redgrave

Chapters
00:27 — Welcome to AI Resistance and Business Uncertainty
01:29 — What Leaders Are Actually Seeing in AI Implementation
04:25 — The Matthew Effect: Early Adopters Gain Compounding Advantages
07:22 — Building Confidence Through Curiosity Instead of Knowing
13:58 — Finding Your Coalition of the Willing
17:27 — AI as Service to Strategy, Not Strategy Itself
20:02 — Trust Challenges in Rapidly Changing Environments
25:07 — Personal Resistance and Overcoming Information Overload
31:57 — Leadership Mindset Shifts for AI Adoption
37:46 — From Systems of Engagement to Systems of Action
39:18 — Practical Steps to Start Your AI Journey
41:12 — Wrap-Up: Commitment, Courage and Capabilities

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Meet the Crew

Mike Richardson – Agility, Peer Power & Collective Intelligence
Website: https://mikerichardson.live/
LinkedIn: https://www.linkedin.com/in/agilityexpertmikerichardson/

Ryan Niemann – Software CEO & Board Operator
Website: https://bob3.pro/
LinkedIn: https://www.linkedin.com/in/ryanniemann/

Mark Redgrave – Agility, People and Performance
Website: https://www.shift-transform.com/
LinkedIn: https://www.linkedin.com/in/mredgrave/

Tom Adams – Executive Coach, Advisor & Trail Blazer
Website: https://tomadams.com/
LinkedIn: https://www.linkedin.com/in/tomadamscoach/

Most companies struggle with AI implementation, treating it as magical solution rather than strategic transformation. This episode reveals that true AI native enterprises are fundamentally redesigned around artificial intelligence at their core, not just bolting on AI features. The discussion focuses on how executives can identify strategic pockets where AI can reshape work processes, customer service, and sales operations. Key concepts include the distinction between AI-native versus AI-enabled businesses, the critical role of skunk works projects for innovation, and overcoming organizational resistance through courageous leadership. Learn why 90-95% of AI proof-of-concept projects fail to scale and how to avoid common pitfalls while creating meaningful business impact.

Highlights

• AI native means core business value couldn't exist without artificial intelligence
• Create physical and mental separation through skunk works projects for true innovation
• Focus AI implementation on back-office operations for maximum business value
• Shift from "why can't we" to "how can we" mindset to overcome risk barriers
• Prioritize AI initiatives with regular scrum meetings and executive commitment
• Start with personal AI use cases to build team engagement and familiarity
• Lead with bold vision rather than incremental goals for transformative change

Important Concepts and Frameworks

• AI Native Enterprise — Organizations built from the ground up with AI as core business value
  • Link: https://www.linkedin.com/pulse/understanding-ai-native-businesses-organisations-olena-zanichkovska-p57vf/
• Skunk Works — Small, autonomous teams working on advanced innovation projects
  • Link: https://en.wikipedia.org/wiki/Skunkworks_project
• Proof of Concept Scaling — Process of expanding successful AI experiments to enterprise level
  • Link: https://www.imaginarycloud.com/blog/axiom-ai-proof-of-concept
• Collective Intelligence — Shared intelligence emerging from AI and human collaboration
  • Link: https://en.wikipedia.org/wiki/Collective_intelligence
• Vision-Led Leadership — Driving transformation through bold future-state vision rather than incremental goals
  • Link: https://www.forbes.com/sites/brentgleeson/2025/05/13/how-bold-leadership-vision-drives-growth-and-talent-driven-cultures/

Tools & Resources Mentioned

• Cursor — AI-native coding environment built from ground up on artificial intelligence
  • Link: https://cursor.sh/
• Sprinklr — Customer experience platform positioning as AI-native solution
  • Link: https://www.sprinklr.com/
• SentinelOne — Cybersecurity platform framing detection as AI-native capability
  • Link: https://www.sentinelone.com
• Better.com — Mortgage lender branding as AI-first financial service provider
  • Link: https://better.com/
• Amira — AI-powered reading assistant showing 4-14% proficiency gains in education
  • Link: https://amiralearning.com/
• ChatGPT — AI assistant used for rapid legal compliance research and document generation
• Evry — Company building AI-native products through newsletter-driven development

Calls to Action

1. Establish regular AI scrum meetings with key stakeholders to maintain momentum and accountability
2. Create physical or mental separation through dedicated innovation spaces or teams
3. Identify one back-office process for AI transformation pilot within the current quarter
4. Encourage team members to experiment with AI for personal tasks to build familiarity
5. Shift risk conversations from "why can't we" to "how can we" with legal and compliance teams
6. Set bold vision targets that require fundamental business model redesign rather than incremental improvement

Key Quotes

• "AI native means the core value of the company could not exist without AI" — Mark Redgrave
• "Don't get hung up on whether you're native or not - focus on using AI" — Mark Redgrave
• "Create separation to reimagine how your business operates" — Mark Redgrave
• "The biggest risk is tickling AI rather than tackling it" — Mike Richardson
• "AI agents don't circumvent process - they require clarity" — Tom Adams

Chapters

00:25 — Introduction to AI Native Enterprise Transformation
05:34 — The Danger of Treating AI as Magic Solution
07:18 — Hollywood's Reaction to Synthetic AI Actress
12:42 — Practical AI Use Case: Legal Compliance Research
13:56 — AI Transforming Education Through Reading Assistance
15:20 — Defining True AI Native Business Models
17:34 — Why Most Companies Cannot Be Truly AI Native
19:40 — EV Platform Analogy for Ground-Up AI Design
24:20 — Skunk Works Approach to AI Innovation
28:07 — Vision-Led Leadership for Transformative Change
32:29 — Overcoming Organizational Risk and Resistance
35:04 — From Tickling to Tackling AI Implementation
39:10 — Executive Playbook for AI Priority and Action
43:12 — Summary and Key Implementation Takeaways

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Meet the Crew

Mike Richardson – Agility, Peer Power & Collective Intelligence
Website: https://mikerichardson.live/
LinkedIn: https://www.linkedin.com/in/agilityexpertmikerichardson/

Ryan Niemann – Software CEO & Board Operator
Website: https://bob3.pro/
LinkedIn: https://www.linkedin.com/in/ryanniemann/

Mark Redgrave – Agility, People and Performance
Website: https://www.shift-transform.com/
LinkedIn: https://www.linkedin.com/in/mredgrave/

Tom Adams – Executive Coach, Advisor & Trail Blazer
Website: https://tomadams.com/
LinkedIn: https://www.linkedin.com/in/tomadamscoach/

CEOs and leaders face the critical challenge of navigating AI transformation while managing costs and organizational change. The reality is that while 80% of organizations explore AI pilots, only 40% successfully deploy them, creating a gap between ambition and execution. Agentic AI—systems that autonomously accomplish goals rather than just completing tasks—promises immense productivity gains but comes with significant cost considerations that can quickly derail budgets.

The conversation reveals that businesses must avoid the "loudest voice trap" where AI investments disproportionately target sales and marketing despite back-office operations offering more demonstrable ROI. Leaders need to embrace self-disruption before external forces mandate it, as demonstrated by Fiverr's public transformation announcement to create "AI-first teams" despite painful personnel reductions. The key is moving from analysis paralysis to action through focused experiments and capability building, with companies like Accenture training 700,000 employees on agentic AI to stay competitive.

Highlights

- Agentic AI development costs can escalate rapidly, requiring diversified tool strategies
- Better-faster-cheaper framework identifies overlapping opportunities for AI implementation
- Weekly executive meetings about AI transformation double the likelihood of successful change
- 95% of agentic AI projects currently fail to deliver significant business impact
- Training existing staff prevents talent shortages and builds internal AI capabilities

Important Concepts and Frameworks

- Agentic AI — Autonomous systems that accomplish goals rather than just completing tasks
  - Link: https://news.microsoft.com/source/features/ai/ai-agents-what-they-are-and-how-theyll-change-the-way-we-work/

- Better-Faster-Cheaper Framework — Triangulating business improvement opportunities
  - Link: https://medium.com/initialized-capital/better-faster-cheaper-cf510c1fc32

- AI-Driven Leader Methodology — Strategic approach to AI transformation
  - Link: https://www.aileadership.com/book

- Conversation Flow to Cash Flow — Regular executive dialogue driving AI implementation
  - Link: https://arya.ai/blog/ai-in-cash-flow-forecasting

Tools & Resources Mentioned

- Fiverr — Marketplace for freelancers undergoing AI-first transformation
  - Link: https://www.linkedin.com/pulse/fiverr-going-back-startup-mode-micha-kaufman-jfe6f/

- Pragmatic Coders — Source for AI implementation statistics and research
  - Link: https://www.pragmaticcoders.com/resources/ai-agent-statistics

- BCG AI Research — Comprehensive AI statistics and growth projections
  - Link: https://www.bcg.com/capabilities/artificial-intelligence/insights
  - https://www.bcg.com/capabilities/artificial-intelligence/ai-agents

- McKinsey AI Insights — Research on AI deployment and organizational impact
  - Link: https://www.mckinsey.com/capabilities/quantumblack/how-we-help-clients

- Accenture AI Training — Large-scale employee upskilling programs
  - Link: https://www.linkedin.com/pulse/training-workforce-accentures-700000-staff-talent-gap-prasad-wbbuc/     
  - https://www.youtube.com/shorts/pJpdH9P2ars

- Arogon.ai - AI headshot generator
   - Link: https://www.aragon.ai/

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Calls to Action

1. Conduct a better-faster-cheaper brainstorming session to identify AI implementation opportunities
2. Establish weekly executive meetings dedicated to AI transformation progress
3. Run focused experiments on one identified opportunity rather than attempting broad implementation
4. Develop internal training programs to build AI capabilities within existing teams
5. Create small, productive AI-first teams to drive organizational change

Key Quotes

- "Self-disrupt before the world does it for you" — Mike Richardson
- "AI is the doorway drug to agentic transformation" — Tom Adams
- "Conversation flow is cash flow in AI implementation" — Ryan Neimann
- "Train your people rather than waiting to hire expensive talent" — Mark Redgrave

Chapters

00:28 — Introduction: Navigating AI Transformation Challenges
02:38 — Better-Faster-Cheaper Framework for AI Implementation
04:15 — Agentic AI Costs and Development Realities
05:44 — Defining Agentic AI: From Tasks to Goals
07:51 — The AI Awareness Gap: Inside vs. Outside Perspectives
14:45 — Fiverr's Public Transformation Announcement Case Study
18:00 — Self-Disruption Strategy: Leading Change Before It's Forced
25:54 — BCG Statistics: AI Growth Projections and Implementation Gaps
28:15 — Sales vs. Back-Office AI Investment Priorities
33:36 — Accenture's 700,000 Employee Training Initiative
35:29 — Building AI Capability Through Progressive Implementation
38:44 — Talent Strategy: Training vs. Hiring in AI Transformation
41:09 — Actionable Frameworks for Immediate AI Implementation
43:31 — The Importance of Experimentation and Learning by Doing
44:11 — Executive Priority Setting for AI Success

Meet the Crew

Mike Richardson – Agility, Peer Power & Collective Intelligence
Website: https://mikerichardson.live/
LinkedIn: https://www.linkedin.com/in/agilityexpertmikerichardson/

Ryan Niemann – Software CEO & Board Operator
Website: https://bob3.pro/
LinkedIn: https://www.linkedin.com/in/ryanniemann/

Mark Redgrave – Agility, People and Performance
Website: https://www.shift-transform.com/
LinkedIn: https://www.linkedin.com/in/mredgrave/

Tom Adams – Executive Coach, Advisor & Trail Blazer
Website: https://tomadams.com/
LinkedIn: https://www.linkedin.com/in/tomadamscoach/

Many professionals struggle with getting meaningful results from AI tools, often settling for generic responses that don't address their specific needs. This episode reveals how strategic prompt engineering transforms AI from a simple question-answering tool into a powerful thought partner for decision-making and productivity. The hosts demonstrate how different language models respond uniquely to the same prompt, showcase custom instruction techniques in ChatGPT, and provide a structured "magic prompt" framework that forces AI to clarify requirements before delivering tailored responses. Learn practical methods to elevate your AI literacy, compare LLM capabilities, and implement enterprise-ready prompt structures that eliminate guesswork and deliver actionable insights.

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Highlights
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• Different LLMs produce dramatically varied responses to identical prompts, revealing their underlying programming biases
• Custom instructions in ChatGPT settings can transform generic interactions into structured, clarifying conversations
• The "magic prompt" framework forces AI to ask three clarifying questions before delivering refined responses
• Poe.com provides access to multiple language models for comparative analysis and capability testing
• Strategic prompt engineering turns AI into a decision-making partner rather than just an information source

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Important Concepts and Frameworks
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• Prompt Completion Guidelines (PCG) - A structured framework that makes AI ask clarifying questions before responding. Here's Ryan's example of a Magic Prompt as shared. 
• Custom Instructions - Settings that personalize how AI models interact with users across conversations. Use Ryan's Magic Prompt as an example. 
• Comparative LLM Analysis - Testing different language models against the same prompt to understand their strengths
• AI Literacy - The ability to effectively communicate with and leverage AI tools for strategic thinking

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Tools & Resources Mentioned
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• Poe.com - Platform providing access to multiple language models for comparison testing
  • Link: https://poe.com/
• GitHub - Code repository platform for sharing and collaborating on technical projects
  • Link: https://github.com/
• AI Driven Leader by Jeff Woods - Book exploring AI as a strategic thinking supplement
  • Link: https://www.amazon.com/AI-Driven-Leader-Harnessing-Smarter-Decisions/dp/B0DB8QL3ZK
• Warp - Terminal tool for developers that enhances coding productivity
  • Link: https://www.warp.dev/
• Super Whisper - Voice-to-text tool that creates prompts based on voice input
  • Link: https://superwhisper.com/

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Calls to Action
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1. Start with familiar topics when testing new prompt structures to better evaluate AI response accuracy
2. Explore the settings and personalization options in your preferred AI tools to customize interactions
3. Create an inventory of effective prompts that work across different platforms and use cases
4. Choose one business process or task to optimize using AI, applying the triangulation approach for better/faster/cheaper solutions
5. Test the same prompt across multiple LLMs using Poe.com to understand different model capabilities

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Key Quotes
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• "AI is a strategic thinking supplement and thought partner for decision making" — Mike Richardson
• "Tiny prompts can hide big needs" — Ryan Neimann
• "The more I put in, the more I get out - worth spending extra minutes putting in" — Mike Richardson
• "Custom instructions transform how you work with LLMs ensuring impactful responses" — Ryan Neimann
• "Get to know your tool settings - most people use only 10% of capability" — Tom Adams

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Chapters
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00:00 - Introduction to AI, Code and Culture Discussions
01:22 - Team Updates and Current AI Exploration Projects
06:52 - Demonstrating Different LLM Responses to Identical Prompts
10:52 - Comparative Analysis of GPT-3.5 vs GPT-4 Responses
12:56 - Grok's Unique Thinking Process Revealed
16:17 - Claude's Writer-Focused Approach to Prompt Completion
18:12 - Deep Seek's Extensive Analysis and Safety Considerations
21:46 - Custom Instructions and Settings Optimization in ChatGPT
25:05 - Implementing the Magic Prompt Framework
28:34 - Practical Business Applications of Structured Prompting
32:06 - Project-Based Prompt Management Across Platforms
35:39 - GitHub Explained Through AI-Generated Metaphors
38:18 - Connecting Prompt Clarification to Peer Group Dynamics
39:16 - Actionable Next Steps for Prompt Engineering Mastery
44:02 - Closing Recommendations and Resource Access

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Meet the Crew
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Mike Richardson – Agility, Peer Power & Collective Intelligence
Website: https://mikerichardson.live/
LinkedIn: https://www.linkedin.com/in/agilityexpertmikerichardson/

Ryan Niemann – Software CEO & Board Operator
Website: https://bob3.pro/
LinkedIn: https://www.linkedin.com/in/ryanniemann/

Mark Redgrave – Agility, People and Performance
Website: https://www.shift-transform.com/
LinkedIn: https://www.linkedin.com/in/mredgrave/

Tom Adams – Executive Coach, Advisor & Trail Blazer
Website: https://tomadams.com/
LinkedIn: https://www.linkedin.com/in/tomadamscoach/

In this episode of Prompt and Circumstance, Tom Adams, Mike Richardson, Mark Redgrave, and Ryan Niemann dig into the art and science of prompting. They share stories of building real tools without coding, debate the importance of prompt discipline, and outline frameworks that every CEO should know as AI becomes core to business strategy.

The crew covers:
- Tom’s no-code apps built in Warp for personal healthcare tracking and in Claude Code for field reps.
- Mark’s perspective on compute costs and why clarity in prompting equals clarity in leadership.
- Ryan’s frameworks—from “Act as a / I will / You will” to the six-component model of prompts.
- Mike’s experiments with Plaud AI recorders and his new Surface AI laptop.

They close with doable actions for CEOs: treat prompting as a core business skill, solve small recurring problems with AI, and form internal councils to experiment with AI capabilities.

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Show Links
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TOOLS & PLATFORMS
- PromptWorks Pro (six-component prompt builder) – https://promptworks.pro
- ChatGPT (OpenAI) – https://chatgpt.com/
- Claude Code (Anthropic) – https://docs.anthropic.com/en/docs/claude-code/overview
- Microsoft Copilot – https://copilot.microsoft.com/
- Perplexity AI – https://www.perplexity.ai/
- Warp (AI terminal) – https://warp.dev
- Plaud AI (recorder) – https://www.plaud.ai/
- Whisper (speech-to-text by OpenAI) – https://openai.com/research/whisper

CONCEPTS & FRAMEWORKS
- Prompt Engineering – https://www.promptingguide.ai/
- “Act as a / I will / You will” structure
- Iterative prompt refinement (“Improve my prompt” technique)
- Agentic AI and conversational vs. product prompting – https://en.wikipedia.org/wiki/Software_agent
- Six-Component Prompt Framework: Role, Task, Context, Reasoning, Format, Success
- “Think harder about this” (leveraging GPT-5 reasoning toggle)
- "The Frontier Firm" How Intelligence on Tap will rewire business (from Microsoft’s Worklab research and Work Trend Index Annual Report)

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Key Quotes
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Mike Richardson
- “If you are able to keep up with me, you’ll be kind of keeping up with them … I’ll do my best to hang on to their coattails.”
- “I got myself one of these Plaud AI recording devices … I’ve just started experimenting with keeping it on all day.”
- “I’ve had more glitches to work through with a brand-new laptop than ever before.”
- “Doing conversational prompts in ChatGPT, Copilot, Claude … that’s good training. We’ll reap the benefits of that when we move to agentic stuff.”
- “Whether you’re using Plaud AI or Copilot … I urge you to get in the habit of using AI companions for every meeting you have.”

Mark Redgrave
- “Before 2010, AI compute doubled every 21 months. Now it’s every 5.3 months … one estimate has the cost surpassing the entire US GDP by 2037.”
- “If you can’t describe what you want, maybe you don’t have the clarity you need … prompting becomes a proxy for whether you understand what you want.”
- “You should be prepared to sit and take time to write a great prompt … I force myself to slow down, even when I want to just hit enter.”
- “Prompting is gonna be table stakes … every team member is going to need to know how to prompt effectively.”

Ryan Niemann
- “Act as a … I will … You will.”
- “If you provide a prompt and then say, would you improve my prompt before proceeding? … it will.”
- “You can also say, ask me three questions before you proceed … it really improves the results you get back.”
- “Role, task, context, reasoning, format, and success — those six components can help improve your prompts.”
- “Try different LLMs … put the same prompt in ChatGPT, then Claude, then Perplexity, and see the different styles you get back.”
- “Think harder about this … you can trigger that in GPT-5 to get deeper reasoning.”

Tom Adams
- “Basically what I built without knowing how to code … was an app that allowed her to voice her challenges … it transcribes it, sends it to AI … and then we’ve been actually taking that to our medical appointments.”
- “We got this problem, like my field reps don’t say something when they see something. And I said, let’s build an app called When You See Something, Say Something.”
- “I don’t know how to code … and yet I’m able to come up with this stuff in hours, maybe even minutes.”
- “Often how we have to converse with a person that we’re asking to do a specific thing … that’s what’s so profound about this — teaching a machine in the way we’d teach a human.”
- “I literally spend all my day just talking … prompts all the time.”

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Doable Actions
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- For CEOs (Mark): Treat prompting as a core business skill. Start building capability across your teams.
- For Practitioners (Tom): Don’t chase big AI projects—solve a small recurring pain point with prompts or agents.
- For Leaders (Ryan): Create an AI council or small working group to explore use cases and grow internal expertise.
- For Individuals (Mike): Start using AI meeting companions daily to capture action items, tone, and productivity insights.

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Meet the Crew
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Mike Richardson - Agility, Peer Power & Collective Intelligence
https://mikerichardson.live/
https://www.linkedin.com/in/agilityexpertmikerichardson/

Ryan Neimann - Software CEO & Board Operator
https://bob3.pro/
https://www.linkedin.com/in/ryanniemann/

Mark Redgrave - Agility, People and Performance
https://www.shift-transform.com/
https://www.linkedin.com/in/mredgrave/

Tom Adams - Executive Coach, Advisor & Trail Blazer
https://tomadams.com/
https://www.linkedin.com/in/tomadamscoach/

In the inaugural episode of 'Prompt and Circumstance,' four seasoned business leaders—Tom Adams, Mike Richardson, Mark Redgrave, and Ryan Niemann—gather around a virtual roundtable to discuss the tumultuous and exciting world of AI.

They introduce themselves, share their backgrounds, and dive into how AI is rapidly transforming industries, impacting CEO decision-making, and fundamentally altering business landscapes.

From AI skepticism to its groundbreaking potential, they highlight personal anecdotes, industry insights, and the importance of hands-on experimentation with AI technologies.

Join them for a no-hype, real-talk discussion about code, culture, and the future of AI in the business world.

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Show Links
TOOLS & PLATFORMS
- ChatGPT (OpenAI’s conversational AI) – https://chatgpt.com/
- Claude Code (Anthropic’s AI coding assistant) – https://docs.anthropic.com/en/docs/claude-code/overview
- Microsoft Copilot (AI assistant across Microsoft 365) – https://copilot.microsoft.com/
- Replit (online coding platform with custom .md instructions) – https://replit.com
- Warp (AI-enhanced terminal) – https://warp.dev
- Plaud (AI-powered transcription tool) – https://www.plaud.ai/
- Limitless (AI pendant) – https://www.limitless.ai/new
- Cursor (AI code editor) – https://cursor.com/

CONCEPTS & FRAMEWORKS
- Prompt Engineering – https://www.promptingguide.ai/
- Iterative Prompt Improvement (“improve my prompt” technique) - https://www.promptlayer.com/glossary/prompt-iteration
- Vibe Coding (experimenting with AI without formal coding background) - https://en.wikipedia.org/wiki/Vibe_coding
- Gartner Hype Cycle – https://en.wikipedia.org/wiki/Hype_cycle
- Dunning–Kruger Effect – https://en.wikipedia.org/wiki/Dunning–Kruger_effect
- VUCA (Volatility, Uncertainty, Complexity, Ambiguity) – https://en.wikipedia.org/wiki/VUCA

KEY QUOTES
- “I really don’t like that fellow… I must get to know him better.” - Paraphrased Mark Twain
- “I’m willing to be the slow guy in the room… but keep up with me, and you’ll be fine.” -  Mike Richardson
- “This is under-hyped.” – Keith Strier (AMD)
- “I’m not a brilliant person. But with AI, I can do brilliant things.” – Claire Gibbon (AWS)
- “Circumstances are the direct result of prompt effectiveness.” – Tom Adams

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Meet The Crew

Mike Richardson - Agility, Peer Power & Collective Intelligence
https://mikerichardson.live/
https://www.linkedin.com/in/agilityexpertmikerichardson/

Ryan Neimann - Software CEO & Board Operator
https://bob3.pro/
https://www.linkedin.com/in/ryanniemann/

Mark Redgrave - Agility, People and Performance
https://www.shift-transform.com/
https://www.linkedin.com/in/mredgrave/

Tom Adams - Executive Coach, Advisor & Trail Blazer
https://tomadams.com/
https://www.linkedin.com/in/tomadamscoach/