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In this episode, Frank La Vigne sits down with his Red Hat colleague Christopher Newland for a deep dive into the evolving challenges and opportunities at the intersection of AI, open source, and enterprise technology.
Fresh off attending both IBM Think and Red Hat Summit, Christopher Newland shares insights from two very different industry perspectives—executive strategy and hands-on engineering. Together, they explore the elusive “last mile” problem in AI adoption, the rise of agentic systems, the critical role of harnesses and runtimes, and why memory management is becoming the next frontier.
Plus, they discuss the practical realities and future potential of tools like OpenShift AI, IBM Bob, and open source alternatives. Whether you’re a developer grappling with implementation details or a leader focused on ROI, this episode has something for everyone navigating today’s fast-changing AI landscape.
Links00:00 Comparing IBM Exec and Red Hat Conferences
05:24 Challenges in AI implementation
06:56 Challenges in scaling microservices
11:38 Integrating AI with project management
14:23 Debate on AI model vs. harness
16:54 Discussing model evolution and limitations
22:54 Affordable Power BI Courses Bundle
25:19 Separating and managing runtimes
27:02 Using semantic routing for requests
30:15 Agent memory and compression basics
36:02 New AI approach and vision
38:49 Developing a multi-agent system
40:40 Importance of data chunking
By Data Driven4.8
4545 ratings
In this episode, Frank La Vigne sits down with his Red Hat colleague Christopher Newland for a deep dive into the evolving challenges and opportunities at the intersection of AI, open source, and enterprise technology.
Fresh off attending both IBM Think and Red Hat Summit, Christopher Newland shares insights from two very different industry perspectives—executive strategy and hands-on engineering. Together, they explore the elusive “last mile” problem in AI adoption, the rise of agentic systems, the critical role of harnesses and runtimes, and why memory management is becoming the next frontier.
Plus, they discuss the practical realities and future potential of tools like OpenShift AI, IBM Bob, and open source alternatives. Whether you’re a developer grappling with implementation details or a leader focused on ROI, this episode has something for everyone navigating today’s fast-changing AI landscape.
Links00:00 Comparing IBM Exec and Red Hat Conferences
05:24 Challenges in AI implementation
06:56 Challenges in scaling microservices
11:38 Integrating AI with project management
14:23 Debate on AI model vs. harness
16:54 Discussing model evolution and limitations
22:54 Affordable Power BI Courses Bundle
25:19 Separating and managing runtimes
27:02 Using semantic routing for requests
30:15 Agent memory and compression basics
36:02 New AI approach and vision
38:49 Developing a multi-agent system
40:40 Importance of data chunking

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