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
Revolutionizing Team Coordination with Steady featuring Henry Poydar
Agile and Project Management - DrunkenPM Radio
54 minutes 27 seconds
3 months ago
Revolutionizing Team Coordination with Steady featuring Henry Poydar
In this conversation, Henry Poydar joins Dave on the podcast to discuss the innovative platform Steady, which aims to enhance team coordination and communication in the workplace. Henry shares his extensive background in engineering and web development, emphasizing the importance of context and intentions in project management. They explore the challenges of cross-team coordination, especially in the wake of the pandemic, and how Steady seeks to unburden teams from the coordination crisis. The discussion also highlights the concept of 'echoes' as a new way to provide contextual insights and the significance of celebrating individual contributions within teams. Overall, the conversation sheds light on the future of work and the role of technology in fostering collaboration and productivity.
Takeaways
- The importance of context in team coordination cannot be overstated.
- Intentions should be prioritized over commitments in project management.
- Writing down intentions serves as a forcing function for clarity.
- The pandemic has highlighted the need for better cross-team coordination.
- Steady aims to unburden teams from coordination challenges.
- The concept of a shared brain can enhance teamwork and communication.
- Echoes are a new way to provide contextual insights to team members.
- Nudges can help optimize workflows and improve productivity.
- Celebrating individual contributions is essential for team morale.
Chapters
04:22 Introduction to Steady and Henry's Background
07:25 The Evolution of Engineering and Design in Tech
10:17 The Importance of Context in Team Coordination
13:05 Intentions vs. Commitments in Project Management
16:08 The Role of Writing in Clarifying Intentions
18:55 The Impact of the Pandemic on Team Dynamics
22:07 Cross-Team Coordination Challenges
25:04 The Cost of Poor Coordination in Knowledge Work
27:54 Steady's Approach to Reducing Coordination Burden
30:58 Creating a Shared Brain for Teams
38:26 Contextualizing Team Dynamics
34:04 Empowering Autonomy in Project Management
39:50 Leveraging AI for Enhanced Collaboration
43:27 The Importance of Personal Recognition
46:00 Tailored Insights for Effective Decision Making
50:28 Vision for a Meaningful Work Environment
Contacting Henry:
- Steady: https://runsteady.com/
- LinkedIn: https://www.linkedin.com/in/henrypoydar/
Other Links from the Podcast:
- 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
