"The things that cost $100 million at GE 15 years ago can now be done at a 15-person manufacturing business."
Garrett's approach to value creation in lower middle market companies starts with upgrading the basics: Microsoft licensing, cloud storage, Azure services. But with AI tools like Claude, he can now deploy enterprise-grade solutions, like configuring Intune for a 30-person company—in two days instead of two months. The foundation has never been cheaper or faster to build.
"You need your editorial AI agents, your fact-checking AI agents. Break down roles and tasks into multiple agents."
The mental model that AI is a "magic black box" producing perfect outputs from generic inputs is the most overrated aspect of AI today. Garrett argues that implementing AI agents should follow the same structures and processes used for humans. News organizations don't let reporters publish directly to the Wall Street Journal: there's an editorial process. AI systems need the same rigor.
"Every company needs an open claw strategy. Not tomorrow, but you need to be experimenting now."
Within a few years, Garrett predicts it'll be normalized to have group chats where 60% of participants are agents. But that requires solving identity management first. Agents need distinct identities: their own Notion accounts, Gmail addresses, Slack profiles, not fake personas pretending to be human. The security infrastructure for this doesn't fully exist yet, but it's coming.
"Focus too much on ROI per use case, and you're missing the forest for the trees."
Garrett separates AI investments into two categories: (1) LLM-based process automation, where token spend vs. ROI matters immediately, and (2) personal productivity and general-purpose agents, where you need a longer time horizon. The second category requires investment like any training program: you won't see quarterly returns, but year-over-year you'll double your business with flat headcount.
"People go, 'I'll just put the LLM in, it'll be better than a rules engine.' But you need to break that mental model."
One of Garrett's most practical insights: use AI to build comprehensive rules-based systems, not to replace them with LLMs running on every transaction. LLMs can design, build, update, and monitor deterministic processes, but they don't need to be in the execution path burning tokens. The old mental model that rules engines are hard to build no longer applies.
"In a year, the distinction between CTO, CIO, and Chief Digital Officer doesn't matter. The job's always been the same."
As AI democratizes technical capability, leadership roles converge. The "ivory tower" IT leader is gone. You have to be both a great leader and an active builder, using AI tools at a granular level, not just strategically. If you're a CFO who's never done a VLOOKUP, how can you lead a finance team? If you're a CTO who hasn't done the prompting, how can you lead technology?
Stay tuned for more conversations on AI transformation, organizational evolution, and practical implementation strategies on CTO2CTO.