I’m excited to announce the upcoming launch of "Lone Wolf AI League", a new premium Skool community for people determined to become the AI resource inside their company, agency, executive room, board room or marketplace. Inside Lone Wolf AI League, I will share real-world AI strategy, deal strategy, wins, losses, client conversations, consulting realities, business execution, and what it actually takes to compete in the AI economy. This post is an example of the type of content and conversations we will explore inside the community. 🐺 Last night, I came across the Reid Hoffman quote: “If you’re not embarrassed by the first version of your product, you’ve launched too late.” I have seen this quote many times, but last night it brought back a wave of nostalgia because it connects directly to something I have experienced over 30 years of building software, launching companies, and surviving technology disruption. Over the last 30 years, I have built more than 100 software applications, large and small. I have started four technology companies. My first startup, in 1999, raised $100,000 in capital. At the time, that was big money to me. We spent six months building a highly specialized eCommerce SaaS model for the brand merchandising industry. We financed an $80,000 server running Windows NT 4, built on a Classic ASP stack, and later moved to .NET. We wanted to go open source, but MySQL was still in its infancy. Java felt like space-age technology. JSON was just starting to look promising. We were in the middle of a 10-year browser war, and you could not practically email a file larger than 1 MB. After a successful launch, we invested another $100,000 in servers and software. We sold SaaS eCommerce subscriptions for $2,500 per month. We thought we were building the future. Then Yahoo launched website and shopping cart capabilities for about $25 per month, and overnight, the industry shifted beneath our feet. Our model was not only under attack. It took a direct hit because customers saw price, but often did not understand the nuance between small retail websites and enterprise eCommerce.

I’m excited to announce the upcoming launch of “Lone Wolf AI League”, a new premium Skool community for people determined to become the AI resource inside their company, agency, executive room, board room or marketplace. Inside Lone Wolf AI League, I will share real-world AI strategy, deal strategy, wins, losses, client conversations, consulting realities, business execution, and what it actually takes to compete in the AI economy. This post is an example of the type of content and conversations we will explore inside the community. 🐺 I consider ROI, and most customers do as well, to be strictly financial: revenue gained, cost reduced, margin improved, cash flow improved, inventory reduced, or labor avoided. Those are ROI conversations. However, not every valuable project starts with a clear ROI. When faced with this situation, this is how I help the client understand which operational outcomes are important enough to justify moving the project forward. Those outcomes usually fall into three categories: - Capturing tribal knowledge, - Making hidden processes visible - Compressing the time it takes to make decisions. The first operational outcome is capturing tribal knowledge. 🐺 Capturing Tribal Knowledge: Tribal knowledge is no longer just what employees know. Increasingly, it is what employees have built inside personal AI accounts, private prompts, spreadsheets, automations, shortcuts, and informal workflows. If critical process knowledge is being built inside personal accounts, the company may not actually own the operating system its employees are using to get work done. That creates a real business risk. The employee becomes more productive, but the business does not necessarily become more capable. And when that employee leaves, the company may lose both the person and the process. The second operational outcome is bringing opaque processes into the light. 🐺 The Black Box Many companies have processes that technically work, but nobody can clearly explain how decisions are being made.