Data Driven

In this episode, hosts Candace Gillhoolley and Frank La Vigne are joined by Neil Katz, Chief Product Officer at Valantor AI—a four-time Emmy winner whose unconventional journey spans from technology startups to award-winning journalism, and now to the forefront of enterprise AI innovation.

Neil shares his unique perspective on the evolution of AI, from the early days of digital design and machine learning, to building large-scale AI and document intelligence platforms for major organizations. The conversation explores the critical challenges of knowledge extraction, document comprehension, and securing sensitive data in today's era of sovereign AI. Together, they uncover the hidden complexities behind Retrieval-Augmented Generation (RAG), discuss the importance of hybrid search strategies, and reflect on where the field is heading as enterprise needs push the boundaries of what AI can do.

Whether you're a data professional, an AI enthusiast, or just curious about how language models are transforming how we understand information, you won’t want to miss this candid and thought-provoking deep dive into the future of AI and data integrity.

• Neil on LinkedIn -https://www.linkedin.com/in/neilkatz/
• Watch on YouTube -https://www.youtube.com/watch?v=qf8qifz_RL8

00:00 Early career in tech and journalism

04:01 Early consumer AI experiences

06:49 Early AI and machine learning developments

11:43 Anthropic's new findings on AI models

16:15 Data sovereignty in AI systems

19:27 Implementing open source AI models

22:49 Breaking down documents for models

25:45 Understanding the RAG system process

28:47 Challenges in AI data processing

31:22 Challenges in RAG with Insurance Data

36:35 Understanding and managing data security

39:35 Early days with OpenAI GPT

40:48 Explaining vector and similarity search

46:57 The evolution of computing models

47:29 Computing evolution to cloud and edge

In this episode, Frank sits down with Devansh Devansh, founder and head of AI at Iris, whose journey spans from building a thriving tech community of over 10,000 on Substack to developing advanced legal AI tools that revolutionize how lawyers work through complex reasoning.

The conversation explores Devansh Devanche's unconventional path into AI, his experiences navigating the evolving landscape of machine learning, and the unique challenges of creating transparent, trustworthy agentic systems in legal tech. Along the way, we uncover the story behind his distinctive "chocolate milk cult leader" branding, his philosophy on startup building, and why he believes that innovation in AI is more accessible than it may seem.

Whether you’re a technologist, a lawyer, or just curious about the future of AI, this is an episode packed with insight, optimism, and actionable advice.

• Devansh on LinkedIn -https://www.linkedin.com/in/devansh-devansh-516004168/
• Devansh on SubStack -https://substack.com/@chocolatemilkcultleader

00:00 Transitioning to Substack and AI Journey

05:32 Starting to publish research insights

07:37 Connecting with Senior Leaders

13:27 Issues with Legal AI Systems

16:55 Challenges with current AI systems

19:49 Demand for AI in legal and non-legal sectors

23:29 Challenges with AI system state management

24:51 Compounding AI returns over time

30:50 Meeting the CEO of Iris

34:20 Tailoring Startup Strategy to Strengths

36:26 Insights on Cluli's Market Presence

40:27 Opportunities in AI Innovation

42:57 Reflecting on market evolutions

In this episode, the conversation focused on the intersection of data intelligence, artificial intelligence, and philanthropy. A key theme that emerged was the growing importance of data-driven decision making in the nonprofit sector, which, despite representing 5% of the GDP and employing 10% of the American workforce, has lagged behind other industries in the adoption of technology and data practices.

The discussion explored how organizations like Impala are aiming to transform the philanthropic landscape by providing robust data platforms and AI-driven tools to empower both large foundations and small nonprofits. Several points were raised, including the unique challenges philanthropy faces in measuring impact versus the traditional business focus on ROI, the rise of a new generation of data-savvy philanthropists, and how collaborative giving and customized data solutions are shaping a more transparent, effective, and innovative sector.

Tune in as we examine how technology is not just changing the way give, but also who gives, why, and with what outcome—pushing philanthropy into a new age powered by actionable insights and human connection.

• Impala -https://impala.digital/

00:00 Importance of Data and Relationships

03:59 Joining Impala through philanthropy

09:00 Measuring organizational impact

12:15 Engaging younger donors with data

14:38 Impala's role in education analysis

20:24 Empowering small nonprofits with AI

22:50 Impala's AI platform strategy

25:07 Improving investment decisions with AI

28:25 Integrating AI with Data Platforms

32:01 Using AI in philanthropic decisions

34:58 Discussing collaborative giving trends

39:28 Supporting small businesses with tech

42:35 Appreciation and social impact goals

This week, we dive deep into the world of data, decision-making, and uncertainty with Dale Nesbitt, a lecturer at Stanford and principal at Arrowhead Economics.

Drawing on his unique upbringing in a mining town, Dale Nesbitt shares how witnessing raw data collection firsthand shaped his perspective on what it really takes to make informed decisions—hint: it's not just about having more data.

Together, we explore the pitfalls of relying solely on data for critical choices, the importance of understanding probability and risk, and why data-gathering itself is often a noisy and imperfect process.

From commodity pricing and speculation in oil markets to the real-world impact of data-driven decisions in healthcare, Dale Nesbitt reveals why true analytic power comes from combining rigorous analysis, sound judgment, and the right kind of data—not just more of it.

Join us as we challenge myths around "data-driven" decisions, unpack lessons from COVID-era data science, and discover why wisdom of the crowd, probability, and a healthy respect for uncertainty are key to navigating our data-rich world.

Links

• Dale's LinkedIn profile -https://www.linkedin.com/in/dale-nesbitt-b574a83a/
• Watch on YouTube -https://www.youtube.com/watch?v=USOKgv1avHo

Time Stamps

00:00 Growing up in a mining town

05:44 Data as the New Crude Oil

07:31 Estimating and Understanding Stochastic Processes

12:49 Impact of Strait of Hormuz Closure

14:19 Challenges of AI in Economics

17:05 Betting on events and elections

21:43 Bayesian analysis and hydroxychloroquine data

23:28 Understanding data and judgment

26:38 Analyzing data for better decisions

On this episode of Data Driven, hosts Frank La Vigne and Candace Gillhoolley are joined by hardware and open source expert Michael Makowski to discuss the shifting landscape of developer workstations and AI hardware. As Windows usage declines among developers and AI engineers, Linux is experiencing a surge in desktop adoption. Michael takes us inside the latest efforts to make Linux not just accessible, but enterprise-grade—sharing how his team is driving advancements in stability, reliability, and user experience for validated Linux hardware.

We talk about the dramatic improvements in Linux desktop support, the importance of privacy and avoiding surveillance-driven proprietary systems, and the game-changing features coming to market—like automated system rollback and curated app installs. Plus, we explore the current state of gaming on Linux, the technical edge unified memory brings to AI development, and why companies are increasingly opting for supported, Linux-based workstations. Whether you’re Linux-curious, rethinking your hardware choices, or just passionate about the future of developer tools and data engineering, this conversation will equip you for what’s next.

• Mike's Company Website -https://kfocus.org/
• Mike's LinkedIn Profile -https://www.linkedin.com/in/michael-mikowski-7601393/
• Watch this show on YouTube -https://youtu.be/E03EObEa2lQ

00:00 Website security concerns and solutions

05:03 Supporting KDE for long-term stability

09:45 Desktop environment compatibility issues

10:46 Conflicts in desktop environments

15:07 AMD vs Intel & Nvidia Performance

18:58 Showing the production site

23:49 Steam's Linux runtime environment

25:43 Running Windows games on Linux

29:47 Concerns about software privacy issues

33:31 Migrating from Windows challenges

37:48 Setting up machine learning hardware

41:31 Resolving system issues efficiently

42:59 Setting up a VPN correctly

47:40 Running VMs on alternative OS

52:49 Upcoming OS Upgrade Details

56:19 Rigorous testing and development process

57:25 Tuning BTRFS for performance

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.

• 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/

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.

• Ron's LinkedIn profile -https://www.linkedin.com/in/ronlongo/
• TrustLogix Web site -https://www.trustlogix.ai/
• TheDingo -https://www.thedingo.ai/

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.

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

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.

• Daniel on LinkedIn -https://www.linkedin.com/in/smyoo/
• FinMate's Websitehttps://finmate.ai/
• Watch this episode on YouTube -https://youtu.be/NV5zOiOXhI0

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.

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

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