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PODCAST

Practical AI

Practical AI LLC

Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest

technology

All Episodes

49:23

Inside an AI-Run Company

Practical AI ·

2026/02/02

AI agents are moving from demos to real workplaces, but what actually happens when they run a company? In this episode, journalist Evan Ratliff, host of Shell Game, joins Chris to discuss his immersive journalism experiment building a real startup staffed almost entirely by AI agents. They explore how AI agents behave as coworkers, how humans react when interacting with them, and where ethical and workplace boundaries begin to break down.Featuring:Evan Ratliff – LinkedIn, XChris Benson –

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48:23

How is AI shaping democracy?

Practical AI ·

2026/01/27

As AI increasingly shapes geopolitics, elections, and civic life, its impact on democracy is becoming impossible to ignore. In this episode, Daniel and Chris are joined by security expert Bruce Schneier to explore how AI and technology are transforming democracy, governance, and citizenship. Drawing from his book Rewiring Democracy, they explore real examples of AI in elections, legislation, courts, and public AI models, the risks of concentrated power, and how these tools can both

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43:55

Controlling AI Models from the Inside

Practical AI ·

2026/01/20

As generative AI moves into production, traditional guardrails and input/output filters can prove too slow, too expensive, and/or too limited. In this episode, Alizishaan Khatri of Wrynx joins Daniel and Chris to explore a fundamentally different approach to AI safety and interpretability. They unpack the limits of today’s black-box defenses, the role of interpretability, and how model-native, runtime signals can enable safer AI systems. Featuring:Alizishaan Khatri – LinkedInChris Benson –

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51:15

2025 was the year of agents, what's coming in 2026?

Practical AI ·

2026/01/09

In this start-of-year FC episode, Chris and Daniel break down what really mattered in AI in 2025, and what to expect in 2026. They explore the rise of AI agents, the practical reality of multimodal AI, and how reasoning models are reshaping workflows. The conversation dives into infrastructure and energy constraints, the continued value of predictive models, and why orchestration (not just better models) is becoming the defining skill for AI teams. The episode wraps with grounded 2026

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45:53

Beyond chatbots: Agents that tackle your SOPs

Practical AI ·

2025/12/17

As AI reshapes the workplace, employees and leaders face questions about meaningful work, automation, and human impact. In this episode, Jason Beutler, CEO of RoboSource, shares how companies can rethink workflows, integrate AI in accessible ways, and empower employees without fear. The discussion covers leveraging AI to handle routine tasks (SOPs or "plays") and reimagining work for smarter, more human-centered outcomes.Featuring:Jason Beutler – LinkedInChris Benson – Website, LinkedIn,

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45:33

The AI engineer skills gap

Practical AI ·

2025/12/10

Chris and Daniel talk with returning guest, Ramin Mohammadi, about how those seeking to get into AI Engineer/ Data Science jobs are expected to come in a mid level engineers (not entry level). They explore this growing gap along with what should (or could) be done in academia to focus on real world skills vs. theoretical knowledge. Featuring:Ramin Mohammadi – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XSponsors:Shopify – The commerce

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49:18

Technical advances in document understanding

Practical AI ·

2025/12/02

Chris and Daniel unpack how AI-driven document processing has rapidly evolved well beyond traditional OCR with many technical advances that fly under the radar. They explore the progression from document structure models to language-vision models, all the way to the newest innovations like Deepseek-OCR. The discussion highlights the pros and cons of these various approaches focusing on practical implementation and usage.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel

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97:09

Chris on AI, autonomous swarming, home automation and...

Practical AI ·

2025/11/26

This episode is a special crossover between the Practical AI podcast and The Changelog podcast. Chris was recently invited by longtime friends Jerod Santo and Adam Stacoviak, cohosts of The Changelog, to join them on the show. They discuss AI, drones, robotics, swarming technology, and the rise of high-performance edge computing with Rust. Chris points out that open source software, small AI models, and affordable hardware are making home automation and local AI accessible to everyone

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48:59

Beyond note-taking with Fireflies

Practical AI ·

2025/11/19

Fireflies CEO, Krish Ramineni shares how the company is transforming AI-powered note-taking into a deeper layer of knowledge automation. He breaks down the technology behind real-time functionality like Live Assist, the user behavior patterns driving product evolution, and how Fireflies is innovating far beyond meetings. Krish also shares insights on future trends in AI and the potential for hardware integration, emphasizing the ongoing evolution of AI in knowledge work.Featuring:Krish

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52:08

Autonomous Vehicle Research at Waymo

Practical AI ·

2025/11/13

Waymo’s VP of Research, Drago Anguelov, joins Practical AI to explore how advances in autonomy, vision models, and large-scale testing are shaping the future of driverless technology. The conversation dives into the dual challenges of building an onboard driver and testing that driver (via large scale simulation). Drago also gives us an update on what Waymo is doing to achieve intelligent, real-time performance while ensuring proven safety and reliability.Featuring:Drago Anguelov –

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49:41

Are we in an AI bubble?

Practical AI ·

2025/11/10

Dan and Chris unpack whether today’s surge in AI deployment across enterprise workflows, manufacturing, healthcare, and scientific research signals a lasting transformation or an overhyped bubble. Drawing parallels to the dot-com era, they explore how technology integration is reshaping industries, affecting jobs, and even influencing human cognition, ultimately asking: is this a bubble, or just a fizzy new phase of innovation?Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub,

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44:45

While loops with tool calls

Practical AI ·

2025/10/30

Dan and Chris sit down (again) with Jared Zoneraich, co-founder and CEO of PromptLayer, to discuss how prompt engineering has evolved into context engineering (and while loops with tool calls). Jared shares insights on building flexible AI applications, managing tool calls, testing and versioning prompts, and empowering both technical and non-technical users in AI development. Along the way, they dive into coding agents and the “crawl-walk-run” approach to AI deployment.Featuring: Jared

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48:23

Tiny Recursive Networks

Practical AI ·

2025/10/24

In this fully connected episode, Daniel and Chris explore the emerging concept of tiny recursive networks introduced by Samsung AI, contrasting them with large transformer based models. They explore how these small models tackle reasoning tasks with fewer parameters, less data, and iterative refinement, matching the giants on specific problems. They also discuss the ethical challenges of emotional manipulation in chatbots.Featuring: Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel

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54:56

Dealing with increasingly complicated agents

Practical AI ·

2025/10/16

As AI systems move from simple chatbots to complex agentic workflows, new security risks emerge. In this episode, Donato Capitella unpacks how increasingly complicated architectures are making agents fragile and vulnerable. These agents can be exploited through prompt injection, data exfiltration, and tool misuse. Donato shares stories from real-world penetration tests, the design patterns for building LLM agents and explains how his open-source toolkit Spikee (Simple Prompt Injection Kit

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44:04

The impact of AI on the workforce: A state-level case...

Practical AI ·

2025/10/09

Daniel sits down with Chelsea Linder, VP of Innovation and Entrepreneurship at TechPoint, to explore the what AI innovation and impact look like on the ground. They discuss Chelsea's journey from the VC world into economic development/ innovation, the growth of an AI innovation network in Indiana (funded by the SBA), lessons learned from fostering AI communities, and how businesses are actually adapting to AI. Chelsea also shares insights from Techpoints AI workforce impact study, which

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43:35

We've all done RAG, now what?

Practical AI ·

2025/09/29

Longtime friend of the show Rajiv Shah returns to unpack lessons from a year of building retrieval-augmented generation (RAG) pipelines and reasoning models integrations. We dive into why so many AI pilots stumble, why evaluation and error analysis remain essential data science skills, and why not every enterprise challenge calls for a large language model.Featuring:Rajiv Shah – LinkedIn Daniel Whitenack – Website, GitHub, XUpcoming Events: Join us at the Midwest AI Summit on November 13 in

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53:08

Creating a private AI assistant in Thunderbird

Practical AI ·

2025/09/23

In this episode, Daniel and Chris are joined by Chris Aquino, software engineer at Thunderbird to hear the story of how they developed a privacy-preserving AI executive assistant. They discuss various design decisions including remote (but confidential) inference, local encryption, and model selection. Chris A. does an amazing job describing the journey from "let the big LLM do everything" to splitting apart the workflow to be handled by multiple models. Featuring:Chris Aquino –

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46:44

Cracking the code of failed AI pilots

Practical AI ·

2025/09/11

In this Fully Connected episode, we dig into the recent MIT report revealing that 95% of AI pilots fail before reaching production and explore what it actually takes to succeed with AI solutions. We dive into the importance of AI model integration, asking the right questions when adopting new technologies, and why simply accessing a powerful model isn’t enough. We explore the latest AI trends, from GPT-5 to open source models, and their impact on jobs, machine learning, and enterprise

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43:20

GenAI risks and global adoption

Practical AI ·

2025/08/27

Daniel and Chris sit with Citadel AI’s Rick Kobayashi and Kenny Song and unpack AI safety and security challenges in the generative AI era. They compare Japan’s approach to AI adoption with the US’s, and explore the implications of real-world failures in AI systems, along with strategies for AI monitoring and evaluation.Featuring:Rick Kobayashi – LinkedInKenny Song – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Citadel AIRegister for

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43:52

Inside America’s AI Action Plan

Practical AI ·

2025/08/19

Dan and Chris break down Winning the Race: America's AI Action Plan, issued by the White House in July 2025. Structured as three "pillars" — Accelerate AI Innovation, Build American AI Infrastructure, and Lead in International AI Diplomacy and Security — our dynamic duo unpack the plan's policy goals and its associated suggestions — while also exploring the mixed reactions it’s sparked across political lines. They connect the plan to international AI diplomacy and national security

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322 results

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