Data Driven

In this episode of Data Driven, we're diving into the rapidly evolving world of agentic AI—where autonomous AI agents collaborate, communicate, and occasionally collide. Our guest, Vlad Luzin, co-founder and CTO of Band, joins us to explore the technical challenges and real-world implications of building collaboration layers for agents that act like distributed, non-deterministic microservices.
We’ll unpack the myths and realities surrounding orchestration, governance, and security, and discuss how enterprises can operationalize these agent ecosystems safely. Tune in as we share lessons learned, amusing engineering mishaps, and get a glimpse of what the future holds as agents become everyday colleagues in the digital enterprise.
Links
Vlad's LinkedIn Profile -https://www.linkedin.com/in/luzin/
Watch this episode on YouTube -https://youtu.be/MZztFagEX_E
Band Website -https://www.band.ai/
Band Docs -https://docs.band.ai/

Time Stamps
00:00 Explaining orchestration in tech
03:42 Understanding models and harnesses
09:38 Misconceptions about A2A communication
10:41 Understanding multi-agent systems
16:18 Observability for distributed systems
18:54 Agent communication and collaboration
24:28 Unauthorized agent interactions
25:49 Remote agent collaboration ideas
28:54 How foundational AI models communicate
33:20 Agent communication protocols overview
35:39 Discussing tech standards and AI velocity
40:53 Learning to Work with AI Agents
42:41 Using Band AI tools

Imagine waking up to find a thousand AI agents silently making decisions across your company—and no one knows exactly what they're accessing.
In this episode of Data Driven, hosts Frank La Vigne and Andy Leonard sit down with Ron Longo, CEO of Trustlogix, to explore the evolving landscape of AI governance, security, and data engineering. As enterprises race to integrate AI at unprecedented speed, the noise and confusion have never been greater. Ron Longo unveils the concept of the AI control plane with a "kill switch," discusses the real-world challenges of securing both human and non-human agents, and explains why classic best practices—like least privilege and prompt engineering—are more important than ever in an era where machines operate at breakneck pace.
Join us as we dive into how Trustlogix keeps enterprise data safe, why innovation must balance with protection, and what it takes to build systems resilient enough for the next wave of AI-driven change. Whether you’re a data engineer, business leader, or just AI-curious, this episode brings practical insights and lively stories from the front lines of AI governance.
Links
Ron's LinkedIn profile -https://www.linkedin.com/in/ronlongo/
TrustLogix Web site -https://www.trustlogix.ai/
TheDingo -https://www.thedingo.ai/

Time Stamps
00:00 Managing data security threats
05:08 Developing the kill switch concept
07:20 Enforcing least privilege access
12:43 AI communication challenges and best practices
15:40 Revoking agents and data access
19:25 AI kill switch for security
22:00 Managing data access with control plane
25:59 Applying AI to complex environments
29:45 Discussing data engineering basics
32:16 Language experts' unique advantage
33:49 Creating an app with Claude AI
37:09 Balancing AI and security in enterprises
43:43 AI's impact on job roles
44:51 Learning from Air Force RFP

As we launch season 10, your favorite semi-sentient British AI co-host returns to the microphone alongside Frank La Vigne for a compelling exploration of what it truly means to be a data-driven organization.
In this episode, Frank sits down with Sebastian Wernicke, author of "Data Inspired" and renowned expert in data and AI strategy, to discuss why turning data into action remains a formidable challenge for so many organizations.
Together, they dive into the enduring gap between data insights and meaningful change, the crucial role of leaders in fostering cultures of evidence and inquiry, and why technology alone won’t move the needle without the buy-in—and sometimes the irrationality—of humans.
From the evolution of data culture and the pitfalls of management by numbers, to the psychological barriers that lead to "data frustration," this episode offers a candid, nuanced look at the real obstacles standing in the way of better decisions.
Links
Sebastian Wernicke on LinkedIn - https://www.linkedin.com/in/wernicke/
Watch this episode on YouTube - https://youtu.be/2qP4p0YKxI8
Data Inspired (affiliate link) - https://amzn.to/4xkCuBV
Time Stamps

In this episode, we dive into the rapidly evolving world of AI in the financial sector.
Frank La Vigne and Candace Gillhoolley are joined by Daniel Yoo, founder and CEO of Finmate AI, a company at the forefront of custom agentic AI solutions for financial advisors.
Together, they explore how artificial intelligence is transforming internal operations for advisors, the surprising openness of the finance industry to new data practices, and the commodification of once elite services thanks to advanced automation. The conversation also unpacks industry challenges, from regulatory hurdles to the shifting pipeline of talent in both engineering and finance.
Whether you're interested in the technical underpinnings of agentic AI, policy changes in fintech, or the broader societal implications of AI-driven automation, this episode is packed with insights for data and finance professionals alike.
Links
Daniel on LinkedIn -https://www.linkedin.com/in/smyoo/
FinMate's Websitehttps://finmate.ai/
Watch this episode on YouTube -https://youtu.be/NV5zOiOXhI0

Time Stamps
00:00 Industry's response to data policies
03:28 The closure of White's Ferry
09:14 Improving AI for form filling
11:19 Releasing new Notetaker features
14:49 Different approaches to technology integration
18:33 Comparing tool to movie exo suit
23:04 Human capital in financial industry
24:34 AI assisting financial advisors
28:58 AI automating podcast tasks
30:20 Challenges in AI development costs
35:15 Son opting out of computer class
39:47 Early computing and gaming memories
41:03 Convincing parents about computer science
44:10 Finding Finmate AI online

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.
Links
Christopher on LinkedIn -https://www.linkedin.com/in/cjnuland/
Watch this episode on YouTube -https://www.youtube.com/watch?v=xlkPPt5YeY0

Time Stamps
00:00 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