Notes on making AI actually work
Short pieces on where and how AI actually helps a company like yours, and where it doesn't. Written for operators, not for people who follow AI news.
Tariffs, Volatile Costs, Supplier Shifts: Why Your Decision-Making Process Needs AI Now
Most AI conversations focus on speed: faster emails, faster reports, faster data pulls. But the bigger opportunity sits at the decision layer. Here's why your current process for making high-stakes calls might not keep up with what's coming.
ReadWhy PE's New Growth Targets Should Worry Every Home Services Operator
PE-backed companies now need 12% annual EBITDA growth, up from 5%. That puts massive pressure on your competitors to find operational gains they never had to look for. Here's why it matters even if you're independently owned.
ReadWhy Your Team Stopped Using AI, and How Role-Specific AI Environments Fix It
Six months ago, your company bought 25 ChatGPT licenses. Today, one person uses it for emails. Three others opened it twice. Access was never the bottleneck. Here's what's actually missing — and how to build it.
ReadAI Adoption Is Failing the Same Way CRM Did 25 Years Ago
In the early 2000s, companies bought CRM software and told their teams to log everything. Adoption was a disaster. 25 years later, companies are buying AI tools and telling their teams to 'just try it.' Same playbook. Same result.
ReadHow PE-Backed Distributors Are Using AI to Pull Ahead, and How Mid-Market Companies Can Compete
Private equity firms have shifted away from financial engineering. They're now betting on AI-driven decision-making. If you're a $45M distributor competing with PE-backed players, here's how to compete without the seven-figure budget.
ReadWhy Generic AI Tools Fail Sales Teams, and What to Build Instead
Generic AI access doesn't stick. Role-specific systems do. Here's what your sales reps actually need — and why most rollouts never get there.
ReadWhere Should Your Company Start with AI? Find the Asymmetric Opportunity First
When companies ask where to start with AI, I'm always looking for the same thing: the asymmetric opportunity. High impact, low friction. That combination is rarer than you'd think — but when you find it, you've found your first move.
ReadWhy Most AI Pilots Fail in B2B Companies (And What to Do Instead)
Most B2B companies start their AI journey backwards — picking a tool first and then searching for a use case. Here's why that approach fails and what actually works.
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