Dave Prior, Agile Trainer, Consultant and Project Manager
263 episodes
1 week ago
In this conversation, Dave Prior and Hugo Bowne-Anderson discuss the evolving landscape of AI and data science, focusing on the role of AI agents in solving business problems. Hugo shares insights on how to effectively implement AI solutions, the importance of understanding the underlying data, and the need for continuous improvement in AI systems. They also touch on the skills necessary for navigating the AI landscape, the value of collaboration between technical and non-technical teams, and the importance of assessing the value of AI projects. Hugo concludes by offering a course on building AI applications, emphasizing the iterative nature of AI development.
Takeaways
- Hugo emphasizes the importance of data in AI applications.
- AI agents can automate tasks but require human oversight.
- Understanding the problem is crucial before implementing AI solutions.
- Prompt engineering remains a valuable skill alongside learning about agents.
- Consultants should educate clients on practical AI applications.
- AI systems should be built incrementally and iteratively.
- Value assessment in AI projects should focus on efficiency and cost savings.
- Continuous improvement is essential for AI systems to remain effective.
- Experimentation with AI tools can lead to innovative solutions.
- Collaboration between technical and non-technical teams is vital for successful AI implementation.
Chapters
00:00 Introduction to Data and AI Literacy
06:14 Understanding AI Agents vs. LLMs
09:18 The Role of Agents in Business Solutions
12:21 Navigating the Future of AI and Agents
15:24 Consulting and Client Education in AI
18:37 Building Incremental AI Solutions
21:29 The Future of AI Coding and Debugging
24:32 Prototyping with AI: Challenges and Solutions
25:32 Leveraging AI for User Insights and Competitive Analysis
27:29 Understanding Value in AI Development
32:05 The Role of Product Managers in AI Integration
33:00 AI as an Instrument: The Human Element
35:33 Getting Started with AI: Practical Steps for Teams
38:51 Building AI Applications: Course Overview and Insights
Links from the Podcast:
Stop Building AI Agents - Here’s what you should build instead (Article) https://www.decodingai.com/p/stop-building-ai-agents
Anthropic https://www.anthropic.com/engineering/multi-agent-research-system
The Colgate Study https://www.pymc-labs.com/blog-posts/AI-based-Customer-Research
Hugo’s Course (Starts November 3, 2025)
Building AI Applications for Data Scientists and Software Engineers (with a 25% discount)
https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=drunkenpm
(You can use the discount code drunkenpm to get 25% off)
How To Be A Podcast Guest with Jay Hrcsko https://youtu.be/vkNbgwcolIM
Contacting Hugo
LinkedIn https://www.linkedin.com/in/hugo-bowne-anderson-045939a5/
Substack https://hugobowne.substack.com/
Contacting Dave
Linktree: https://linktr.ee/mrsungo
Dave’s Classes: https://www.eventbrite.com/cc/dave-prior-classes-4758623
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In this conversation, Dave Prior and Hugo Bowne-Anderson discuss the evolving landscape of AI and data science, focusing on the role of AI agents in solving business problems. Hugo shares insights on how to effectively implement AI solutions, the importance of understanding the underlying data, and the need for continuous improvement in AI systems. They also touch on the skills necessary for navigating the AI landscape, the value of collaboration between technical and non-technical teams, and the importance of assessing the value of AI projects. Hugo concludes by offering a course on building AI applications, emphasizing the iterative nature of AI development.
Takeaways
- Hugo emphasizes the importance of data in AI applications.
- AI agents can automate tasks but require human oversight.
- Understanding the problem is crucial before implementing AI solutions.
- Prompt engineering remains a valuable skill alongside learning about agents.
- Consultants should educate clients on practical AI applications.
- AI systems should be built incrementally and iteratively.
- Value assessment in AI projects should focus on efficiency and cost savings.
- Continuous improvement is essential for AI systems to remain effective.
- Experimentation with AI tools can lead to innovative solutions.
- Collaboration between technical and non-technical teams is vital for successful AI implementation.
Chapters
00:00 Introduction to Data and AI Literacy
06:14 Understanding AI Agents vs. LLMs
09:18 The Role of Agents in Business Solutions
12:21 Navigating the Future of AI and Agents
15:24 Consulting and Client Education in AI
18:37 Building Incremental AI Solutions
21:29 The Future of AI Coding and Debugging
24:32 Prototyping with AI: Challenges and Solutions
25:32 Leveraging AI for User Insights and Competitive Analysis
27:29 Understanding Value in AI Development
32:05 The Role of Product Managers in AI Integration
33:00 AI as an Instrument: The Human Element
35:33 Getting Started with AI: Practical Steps for Teams
38:51 Building AI Applications: Course Overview and Insights
Links from the Podcast:
Stop Building AI Agents - Here’s what you should build instead (Article) https://www.decodingai.com/p/stop-building-ai-agents
Anthropic https://www.anthropic.com/engineering/multi-agent-research-system
The Colgate Study https://www.pymc-labs.com/blog-posts/AI-based-Customer-Research
Hugo’s Course (Starts November 3, 2025)
Building AI Applications for Data Scientists and Software Engineers (with a 25% discount)
https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=drunkenpm
(You can use the discount code drunkenpm to get 25% off)
How To Be A Podcast Guest with Jay Hrcsko https://youtu.be/vkNbgwcolIM
Contacting Hugo
LinkedIn https://www.linkedin.com/in/hugo-bowne-anderson-045939a5/
Substack https://hugobowne.substack.com/
Contacting Dave
Linktree: https://linktr.ee/mrsungo
Dave’s Classes: https://www.eventbrite.com/cc/dave-prior-classes-4758623
David Marquet - Distancing - How Great Leaders Reframe to Make Better Decisions
Agile and Project Management - DrunkenPM Radio
36 minutes 34 seconds
2 months ago
David Marquet - Distancing - How Great Leaders Reframe to Make Better Decisions
In this conversation, David Marquet shares his transformative leadership journey from commanding the Santa Fe submarine, one of the worst performers in the fleet, to implementing a culture of empowerment and accountability. He discusses the importance of shifting from a language of permission to a language of intent, encouraging leaders to empower their teams to think critically and make decisions. Marquet emphasizes the significance of mindset, distance, and self-coaching in effective decision-making, and how visualizing problems can lead to better solutions. The discussion culminates in practical advice for creating a culture of accountability and fostering a proactive mindset within teams.
Takeaways
Leadership is about inspiring teams, not just giving orders.
The language of permission can stifle innovation and accountability.
Empower your team to think critically and make decisions.
Mindset and distance are crucial for effective decision-making.
Coaching yourself can lead to better outcomes.
Visualizing problems helps in understanding and solving them.
Creating a culture of accountability is essential for success.
Encourage a language of intent over a language of permission.
Fresh perspectives can lead to innovative solutions.
Transformational leadership requires a shift in mindset and language.
LINKS
Distancing - How Great Leaders Reframe to Make Better Decisions by L. David Marquet and Michael A. Gillespie https://tinyurl.com/wtadnumb
You can check out the interview with David’s co-author, Michael Gillespie, here: https://on.soundcloud.com/zb166tQR3Ce8gp0tHd
Contacting L. David Marquet
Web: https://davidmarquet.com
LinkedIn: https://www.linkedin.com/in/davidmarquet/
Amazon: https://tinyurl.com/4ezbp4a9
Contacting Michael Gillespie
University of South Florida: https://tinyurl.com/yds54cbe
LinkedIn: https://www.linkedin.com/in/michael-gillespie-78661a4/
Agile and Project Management - DrunkenPM Radio
In this conversation, Dave Prior and Hugo Bowne-Anderson discuss the evolving landscape of AI and data science, focusing on the role of AI agents in solving business problems. Hugo shares insights on how to effectively implement AI solutions, the importance of understanding the underlying data, and the need for continuous improvement in AI systems. They also touch on the skills necessary for navigating the AI landscape, the value of collaboration between technical and non-technical teams, and the importance of assessing the value of AI projects. Hugo concludes by offering a course on building AI applications, emphasizing the iterative nature of AI development.
Takeaways
- Hugo emphasizes the importance of data in AI applications.
- AI agents can automate tasks but require human oversight.
- Understanding the problem is crucial before implementing AI solutions.
- Prompt engineering remains a valuable skill alongside learning about agents.
- Consultants should educate clients on practical AI applications.
- AI systems should be built incrementally and iteratively.
- Value assessment in AI projects should focus on efficiency and cost savings.
- Continuous improvement is essential for AI systems to remain effective.
- Experimentation with AI tools can lead to innovative solutions.
- Collaboration between technical and non-technical teams is vital for successful AI implementation.
Chapters
00:00 Introduction to Data and AI Literacy
06:14 Understanding AI Agents vs. LLMs
09:18 The Role of Agents in Business Solutions
12:21 Navigating the Future of AI and Agents
15:24 Consulting and Client Education in AI
18:37 Building Incremental AI Solutions
21:29 The Future of AI Coding and Debugging
24:32 Prototyping with AI: Challenges and Solutions
25:32 Leveraging AI for User Insights and Competitive Analysis
27:29 Understanding Value in AI Development
32:05 The Role of Product Managers in AI Integration
33:00 AI as an Instrument: The Human Element
35:33 Getting Started with AI: Practical Steps for Teams
38:51 Building AI Applications: Course Overview and Insights
Links from the Podcast:
Stop Building AI Agents - Here’s what you should build instead (Article) https://www.decodingai.com/p/stop-building-ai-agents
Anthropic https://www.anthropic.com/engineering/multi-agent-research-system
The Colgate Study https://www.pymc-labs.com/blog-posts/AI-based-Customer-Research
Hugo’s Course (Starts November 3, 2025)
Building AI Applications for Data Scientists and Software Engineers (with a 25% discount)
https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=drunkenpm
(You can use the discount code drunkenpm to get 25% off)
How To Be A Podcast Guest with Jay Hrcsko https://youtu.be/vkNbgwcolIM
Contacting Hugo
LinkedIn https://www.linkedin.com/in/hugo-bowne-anderson-045939a5/
Substack https://hugobowne.substack.com/
Contacting Dave
Linktree: https://linktr.ee/mrsungo
Dave’s Classes: https://www.eventbrite.com/cc/dave-prior-classes-4758623
