The AI Guys

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, Head of Market and Product Strategy 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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What happens when AI adoption goes up, but business results do not? In this episode of The AI Guys Podcast, Lee and Rich break down why so many companies are pouring money into AI tools, burning through tokens, and still struggling to connect that spend to real outcomes. They unpack the shift from basic tool adoption to a more agentic, centralized approach that actually gives businesses visibility, control, and a path to ROI.

The conversation centers on four key lenses businesses should use to evaluate AI: dependency, cost, outcome, and scalability. Lee and Rich dig into vendor lock in, the rising reality of token spend as the new cloud bill, the danger of duplicated work across teams, and why centralized AI infrastructure beats letting disconnected tools run wild at the edge of the company. They also explore why faster coding does not automatically mean faster shipping, and why AI usage without accountability can quickly turn into expensive noise.

If your team is trying to become AI native without losing control of cost, workflow, or strategy, this episode is for you. Subscribe for more conversations that make artificial intelligence easy to understand, and check out the links below for more resources.

00:00 Introduction

00:17 The Evolution of AI in Business

00:50 Understanding AI Deployment Lenses

03:53 Control and Functionality in AI Usage

06:51 Dependency and Cost Management in AI

09:49 Navigating AI Vendor Relationships

12:14 Navigating the SaaS Trap

15:12 Control and Integration in AI

18:43 Shared Organizational Intelligence

21:32 Cost Management in AI Deployment

27:13 Scalability and Future-Proofing AI Strategies
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AI is moving fast, maybe too fast. In this episode of The AI Guys Podcast, Lee and Rich break down why the current AI boom is starting to look a lot like a bubble, and what that means for businesses trying to keep up. From hype-driven valuations to real-world adoption lag, this conversation gets into the growing gap between what AI promises and what companies are actually using in production.

Lee and Rich dig into the bigger market signals shaping the space, including government pressure on frontier models, the strange logic behind massive AI acquisitions, and why pricing, token burn, and overvaluation are becoming impossible to ignore. They also unpack the difference between AI being widely used versus truly adopted, especially inside large organizations with legacy systems, tight budgets, and real operational risk. If your team is experimenting with AI but struggling to measure value, this episode will hit close to home.

If you are trying to separate signal from noise in the AI market, this is the episode for you. Subscribe for more honest conversations on where AI is headed, what businesses should actually pay attention to, and how to avoid getting swept up in the hype.

00:00 Introduction

00:30 Salesforce Acquisitions: Validation or Consolidation?

02:57 SpaceX and the AI Landscape

06:10 Comparative Analysis of AI Acquisitions

10:49 The AI Regulatory Landscape

13:38 The Speed of AI Development

16:45 Business Adaptation to AI

19:40 Valuation and Market Dynamics

22:42 The Reality of AI Adoption

25:38 Measuring AI Impact

28:43 The Future of AI and Consumer Behavior

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What happens when AI lets you build faster than your business can actually adapt? In this episode of The AI Guys, Lee and Rich unpack the gap between rapid AI-powered development and real-world business readiness. They explore why speed alone does not create ROI, and why launching AI products without the right support systems can create more chaos than value.

The conversation digs into the hidden infrastructure behind successful AI adoption, from documentation and legacy code support to training, ticket handling, and operational alignment. Lee and Rich also break down the mindset shift required to become truly AI-native, including motivating teams to use AI, finding practical use cases tied to real pain points, and embracing the messy learning curve that comes with experimentation. This episode is a sharp look at why businesses need more than fast prototypes, they need a full AI ecosystem.

If you’re thinking about how AI fits into your company, this episode will challenge the way you approach adoption, scale, and transformation. Subscribe for more practical AI conversations, and check out these links for more content from The AI Guys.

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