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Navigating AI - Making Sense of Agents and When To Use Them with Hugo Bowne-Anderson

Agile and Project Management - DrunkenPM Radio by drunkenpmradio

Oct 28, 202500:43:21Technology

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 i...

About This Episode

Navigating AI - Making Sense of Agents and When To Use Them with Hugo Bowne-Anderson is an episode from Agile and Project Management - DrunkenPM Radio by drunkenpmradio. In this conversation, Dave Prior and Hugo Bowne-Anderson discuss the e...

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Episode Details

Published Oct 28, 2025, 00:43:21 long, audio available.

Questions About This Episode

What is Navigating AI - Making Sense of Agents and When To Use Them with Hugo Bowne-Anderson about?

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) Anthropic The Colgate Study Hugo’s Course (Starts November 3, 2025) Building AI Applications for Data Scientists and Software Engineers (with a 25% discount) (You can use the discount code drunkenpm to get 25% off) How To Be A Podcast Guest with Jay Hrcsko Contacting Hugo LinkedIn Substack Contacting Dave Linktree: Dave’s Classes:

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Which podcast is Navigating AI - Making Sense of Agents and When To Use Them with Hugo Bowne-Anderson from?

Navigating AI - Making Sense of Agents and When To Use Them with Hugo Bowne-Anderson is an episode from Agile and Project Management - DrunkenPM Radio by drunkenpmradio.

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This episode is 00:43:21 long.

When was this episode published?

This episode was published on Oct 28, 2025.

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Where can I listen to Navigating AI - Making Sense of Agents and When To Use Them with Hugo Bowne-Anderson?

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Which podcast is this episode from?

Navigating AI - Making Sense of Agents and When To Use Them with Hugo Bowne-Anderson is from Agile and Project Management - DrunkenPM Radio by drunkenpmradio.

What are the episode details?

Published Oct 28, 2025 and 00:43:21 long