Pattern Recognized

There is a stage of AI use where you stop doing the task with AI and start building the thing that does the task. Most people do not know it exists. The ones who do mostly assume it is locked behind a computer science degree. In this episode, I explain how anyone can get to Fly-level AI use, creating their own AI tools and Agents.

Every organization that uses AI tools needs a written policy, and most of them do not have one. This episode walks listeners through the exact components of a practical, readable AI use policy that protects the organization without terrifying the staff. You can offer the template as a lead magnet.

Most organizations "do AI" by handing it to the engineers, and six months later nothing about the real work has changed. In this episode, Josh makes the case that AI adoption fails at the human layer, not the machine layer. He explains why most failures are baked in before an engineer ever touches a tool, and why the people best suited to lead adoption are often the ones every org wrote off as a support function. Along the way he draws a hard line: the market took two different jobs, AI implementation and AI adoption, and stapled them into one job description. Whether your rollout stalled or you are realizing the door is open to you, this one is for you.

Everyone wants to know if AI is working. The problem is when they ask, and what they reach for to answer it. Most leaders grab a stopwatch three weeks in and wonder why the numbers are disappointing. They are not measuring the wrong tool. They are measuring the right tool at the wrong time. In this episode, Josh Bechtel walks through how to read the real return on AI investment without getting fooled by the obvious metric. You will learn why "time saved" is a trap in the first month, the crucial difference between efficiency ROI and capability ROI, and exactly what to measure in week one, month one, and month three. Josh also covers how to set expectations with leadership before they pull the plug during the dip, and how to build a simple tracking dashboard using tools you already have. No magic formula. No hype. Just a better way to tell whether your AI investment is heading somewhere worth going.

Prompting is the new literacy and most people are doing it the way they used to Google things: throwing keywords at the screen and hoping. This episode teaches the fundamentals of prompting in plain language, with real before-and-after examples your listeners can try immediately

AI adoption can go sideways before anyone realizes it. In this episode of Pattern Recognized, we break down the five predictable mistakes organizations make in the first week of AI rollout: tool excitement without a plan, one-hour training that never becomes practice, accidental AI departments of one, missing policies, and measuring the wrong things too early. More importantly, we look at how to catch these mistakes early and turn AI adoption into something useful, measurable, and human-centered.

Today on Pattern Recognized, we are talking about AI skill and readiness. Specifically, where you and your organization actually stand in its ability to use AI effectively, and why almost every organization that fails at this misreads its position the same way.

Shadow AI is real and it is happening in many organizations right now. This episode pulls back the curtain on what your staff is already doing with tools like ChatGPT and Claude, why they are doing it quietly, and what that means for your organization. The goal is not to scare leaders but to shift them from reaction to intention.

I am not going to tell you AI is going to change everything. In this episode, I am going to tell you something of what AI actually is, because once you know that, the hype gets a lot easier to ignore and the tools’ power becomes more evident.