FSBO Explained: What the Industry Doesn't Tell You About Selling Your Own Home

Burn tokens, not headcount: how small teams should hear that AI phrase

A phrase from a recent AI talk has been making the rounds: "burn tokens, not headcount." It sounds cold at first. The right way to hear it is one of the most useful framings a small-business owner can carry into the AI era. Armando Perez-Carreno walks through how small teams are getting more leverage from AI than ever before, and where the trap lies. Hiring another coordinator or rep to handle volume can feel like the right move. But what if the workflow itself is the problem? People matter too much to waste their time acting like glue between systems. That's the work AI is genuinely good at, and the work humans should be free to stop doing. This isn't a video about layoffs. It's about asking better questions before you add headcount: which parts of the work belong to a person, and which belong to a system? If your knowledge isn't captured cleanly inside the company, no AI tool will offload much.

Why Your First AI Project Probably Shouldn't Be a Chatbot

Most businesses jump straight to chatbots because they look impressive. But if your underlying workflows are broken, a chatbot just moves the bottleneck somewhere else. In this solo episode, Armando J. Perez-Carreno of PerezCarreno & Coindreau breaks down how to choose the right first AI project for your business, and why it's usually a workflow, not a chatbot. If you want to move past the demos and start building AI that actually works, subscribe so you don't miss the next one.

Does Your Company Already Have An AI Champion?

Most companies are not failing at AI because the tools are bad. They are failing because nobody owns the messy middle between having access to AI and changing how work actually gets done. In this episode, Armando explains why every small and medium business needs an internal AI champion, what that role really looks like, and how to build a repeatable AI adoption muscle inside your company.

If It Wasn't Recorded, It Didn't Happen to Your AI

Your business knows a lot more than your systems do. The problem? If that knowledge lives only in someone's head, your AI can't use it. In this solo episode, Armando breaks down why "AI legibility" is the missing piece behind so many stalled AI projects, and what to capture (and what not to) so your tools can actually produce work that sounds like your company. You'll walk away with a practical starting point for turning expert judgment, repeated decisions, and scattered knowledge into something AI can genuinely help with.

From Demo to Deployment: Where Most Companies Get Stuck

Buying an AI tool is the easy part. Changing the workflow is the hard part. That's why so many AI projects look incredible in demos, then quietly disappear inside the company. In this solo episode, Armando J. Perez-Carreno breaks down the gap between AI demos and real business deployment, and shares the workflow first approach his agency uses with clients. In this conversation, you'll learn: * Why Gartner predicts at least 30% of generative AI projects will be abandoned after proof of concept * The difference between launching an AI system and actually deploying one * A 7 question readiness test to know if your workflow is ready for AI * How to map a workflow before you decide where AI belongs (and where it doesn't) * A real client onboarding example that shows where AI helps and where simple automation is enough * The three kinds of AI tool purchases (personal productivity, team workflow, operating system change) and which one most small businesses should focus on * The exact questions to ask any vendor before signing an AI subscription If you're tired of shiny demos that don't survive contact with real data, this episode gives you a practical filter to make better decisions. Subscribe to The Web Talk Show for more honest conversations about AI, technology, and building real businesses.