What happens when AI collides with one of the most complex industries on earth? In this episode of The AI Guys Podcast, Lee and Rich sit down with Chris Notaro to unpack why healthcare may be one of the biggest battlegrounds for AI, from messy data environments and vendor lock-in to governance, cybersecurity, and the growing gap between innovation and implementation. It is a sharp, honest conversation about what is really holding the industry back, and where the biggest opportunities are starting to emerge.

The team digs into why most healthcare organizations still are not truly ready for AI, how administrative bloat continues to slow progress, and why many of today’s AI wins are happening in billing, claims, and operations instead of direct patient care. Chris also shares his perspective on healthcare data sovereignty, the tension between providers and payers, and how consumers are beginning to use AI tools to take more control over their own health decisions, records, and insurance battles. If you want a real-world look at where AI is creating friction, leverage, and change inside healthcare, this episode delivers it.

If you enjoyed this episode, make sure to subscribe and follow The AI Guys Podcast for more conversations that break down how AI is reshaping business, technology, and everyday life. Drop a comment with your biggest takeaway, and let us know whether AI will fix healthcare, expose its flaws, or both.

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What happens when AI stops being just a tool and starts becoming part of the product building process itself? In this episode of The AI Guys Podcast, Lee and Rich sit down with Tom Carluccio, VP of Product Management at Crosscap, to talk about how AI is reshaping product discovery, prototyping, and software delivery. Tom shares his journey from startups and consulting into product leadership, along with the mindset shift that helped his team move faster and build smarter.

The conversation digs into what it really looks like to build products with AI in the loop. Tom breaks down how rapid prototyping creates better customer feedback, why AI compresses the time between idea and execution, and how teams can stay focused on shipping instead of getting stuck in endless planning cycles. They also get into the real challenges, including legacy systems, internal adoption, developer workflows, quality control, and why deep domain expertise still matters more than ever in an AI-first world.

If you are leading a product team, building software, or trying to figure out how AI actually fits into your business, this episode is packed with practical insight. Subscribe for more conversations that make artificial intelligence easier to understand and easier to apply.

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In this episode of The AI Guys Podcast, Lee and Rich dig into the real cost of AI and why cheaper models do not always mean lower bills. They unpack the "inference paradox," where token prices keep dropping while total AI spend keeps climbing because agents are reasoning more, retrying more, and handling increasingly complex workflows. If your team feels like AI is getting more powerful and more expensive at the same time, this episode will hit home.

The conversation breaks down where businesses waste money with AI, from choosing the wrong model for the job to letting massive context windows balloon token usage without realizing it. Lee and Rich also explore why companies need to stop thinking only about cost per token and start measuring cost per outcome, cost per resolved task, and actual business value. They close with a smart look at model routing, orchestration, budget controls, and why the future of AI depends on sending the right work to the right model at the right time.

If you are building with AI, scaling internal usage, or trying to get control of rising token costs, this episode is packed with practical takeaways. Be sure to subscribe so you do not miss future conversations on AI strategy, infrastructure, and real-world adoption.

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What happens when AI makes coding dramatically faster, but shipping reliable software still takes just as long? In this episode of The AI Guys Podcast, Lee Dickson and Rich Swire dig into the new bottleneck showing up in AI-powered development, verification, QA, and security. It’s a sharp, honest conversation about why faster code does not automatically mean faster product delivery.

Lee and Rich break down how AI is reshaping the software development lifecycle, from writing better specs up front to testing, reviewing, and managing AI-generated code on the back end. They explore the difference between internal tools and mission-critical products, the growing cost of tokens, the rise of modular development, and why the real competitive advantage may come from teams that can validate, secure, and deploy just as fast as they can generate. They also dig into the idea of self-healing software, changing user expectations, and why developers may need to rethink how they work before AI forces the shift
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If you’re leading a product team, building with AI, or trying to understand where software development is headed next, this episode is for you. Subscribe for more practical conversations on AI, business, and the future of work.



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What happens when AI stops being just a tool and starts becoming part of the team? In this episode of The AI Guys Podcast, Lee and Rich sit down with returning guest Richard Partridge of New Line ASP to unpack what real AI transformation looks like inside a business. This conversation goes beyond hype and gets into the shift from casually using AI to building with it, managing it, and creating real operational impact.

The episode explores how teams move from experimentation into structure, including centralizing tools, tracking ROI, controlling token spend, and assigning real ownership to AI agents. Richard shares how different departments, from sales to customer service, are building practical AI solutions, why adoption only works when managers reinforce usage, and how small wins can unlock bigger company-wide momentum. The team also digs into a major truth many businesses are learning right now, AI works best when it amplifies human judgment, not when it tries to replace it.

If you are trying to figure out how to roll out AI inside your company without chaos, this episode is packed with lessons from the front lines. Watch now, then let us know where your team is in the journey from user to builder to manager.


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The AI arms race is entering a new phase, and this episode breaks down why the biggest players are suddenly buying, partnering, and consolidating at full speed. Lee and Rich unpack the pre IPO shopping spree happening across the AI landscape, from frontier model companies chasing platform control to the growing pressure to justify massive valuations.

They dig into what these moves could mean for OpenAI, Anthropic, Google, xAI, and the broader open source ecosystem. Along the way, they explore whether model quality is really improving as much as the hype suggests, why token costs may be more manipulated than most people realize, and how businesses can protect themselves from vendor lock in as AI dependency grows.

If you are trying to understand where the market is heading, this episode gives you a practical lens on the strategy, incentives, and risks behind the headlines. Subscribe to stay in touch, and follow along as The AI Guys keep translating fast moving AI news into real business insight.

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00:28 Market strategies and the race for dominance in AI

05:16 The role of platform building and vertical integration

10:21 Challenges faced by open AI, Anthropic, and Google

15:10 Market dynamics, regulation, and the AI winter

20:09 The importance of control and ownership in AI ecosystems

25:07 The cost paradox and token inflation in AI models

30:21 Market manipulation, hype, and the race for valuation

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What does it really take to build an AI native business right now? In this episode of The AI Guys Podcast, Rich and Lee sit down with Devin Kearns, founder of CustomAI Studio, to unpack the real state of AI agents, why so many early AI products got wiped out fast, and what businesses are still getting wrong as they try to adopt this technology. It is a grounded, honest conversation about where the space is today, and where it is actually headed next.

They dig into the difference between true agents and basic automation, why companies still judge AI more harshly than human employees, and how legacy systems, messy internal data, and weak documentation are slowing adoption down. The conversation also explores AI readiness, the growing importance of capturing unstructured business knowledge, the shift from traditional SaaS thinking to AI native operations, and the rising debate around model pricing, open source models, Chinese AI labs, and token costs as a new form of labor spend.

If you are trying to understand how AI will reshape real businesses, this episode is packed with practical insight and big picture thinking. Let us know your biggest takeaway in the comments, and subscribe for more conversations that make AI easier to understand.

Custom AI Studio (CAIS) is a custom AI consulting and engineering firm that designs, builds, and deploys production AI systems for mid-market and enterprise companies. Unlike off-the-shelf SaaS, every system is built for a single client, who owns all the code, models, and IP outright, with no vendor lock-in and no multi-tenant platform. Since 2024, CAIS has shipped 60+ production deployments.

Website: https://www.customaistudio.io

YouTube: https://www.youtube.com/channel/UCoAnMAQvxQDJ3Wtl3oMLF5Q

Company LinkedIn: https://www.linkedin.com/company/custom-ai-studio

Devin's LinkedIn: https://www.linkedin.com/in/devin-kearns-15895a42/

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What does it actually take to launch AI successfully inside a business? In this episode of The AI Guys Podcast, Lee Dickson and Rich Swier break down the four essential roles every company needs to move AI projects from idea to execution. If your team has been treating AI like a side project, this conversation shows why that approach usually falls apart.

Lee and Rich unpack the functional expert, the technical agent builder, the integration and IT lead, and the agent power user. They explain how each role contributes to building smarter agents, securing system access, improving adoption, and creating feedback loops that help AI tools get better over time. The episode also explores why so many AI initiatives stall before launch, and how the right team structure can dramatically improve your chances of success.

If you are planning to build AI agents in your business, this episode gives you a practical framework to start with. Subscribe for more conversations that make AI easier to understand and easier to implement.

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