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
Building Resiliance with Agile2025 Keynote Speaker Tricia Broderick
Agile and Project Management - DrunkenPM Radio
26 minutes 34 seconds
3 months ago
Building Resiliance with Agile2025 Keynote Speaker Tricia Broderick
Building Resiliance with Agile2025 Keynote Speaker Tricia Broderick
Dave Prior interviews Tricia Broderick for the Agile 2025 pre-conference, focusing on her keynote on building resilience. Tricia discusses the challenges of the current job market, including high unemployment and overworked employees. She emphasizes the importance of resilience and community support. Tricia also highlights the upcoming AI Readiness for Professionals course, starting August 6, which aims to help professionals stay competitive in an AI-driven world. The conversation touches on the emotional toll of supporting others and the need for empathy and practical support. Tricia looks forward to the Agile 2025 conference, particularly the opportunity to honor past community members.
Key Takeaways
- Resilience is essential in our current world of work due to a challenging job market and overwhelming workloads.
- Empathetic people struggle with the emotional toll of trying to support numerous friends and colleagues who are out of work or struggling.
- Community and in-person connections, like at the Agile conference, provide a vital source of restoration and support.
- Building personal resilience can be achieved by focusing on what you can control, such as limiting news consumption and performing small acts of kindness.
- Tricia will use her keynote to honor four mentors who are no longer with us but had a significant generational impact on her career.
To register for Agile 2025
https://agilealliance.org/agile2025/pricing/
Tricia's Links
Details on Tricia's Keynote at Agile 2025
https://tinyurl.com/nuwyk629
Lead Without Blame by Tricia Broderick and Diana Larsen
https://tinyurl.com/bddcxhhd
Tricia's Website
https://igniteii.com/
Tricia on LinkedIn
https://www.linkedin.com/in/tricia-broderick
Links from the Intro
The Agile Network - Live from Agile2025 Lineup
https://tinyurl.com/bdf4n92m
Dave and Stuart's Talk at Agile 2025: Career Power-Ups: Surviving Through Uncertainty and Change
tinyurl.com/2s4zhzts
Dave and Stuart’s Book: “No One Is Coming to Save You”
www.stuartyoung.uk/copy-of-human-skills-1
AI Readiness for Professionals Course
tinyurl.com/y79kassb
Dave’s Upcoming Scrum Certification Classes
www.scrumalliance.org/courses-events…=14153&cnty=US
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
