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Strategy7 min read · March 18, 2026

What Actually Matters in AI Right Now — And What Doesn't

The signal-to-noise problem in AI today — and the few things mid-market operators should actually care about.

DK
Devin Kearns
Peys

The noise in the AI industry is deafening. Every week brings a new model release, a new valuation, or a new agent framework.

If you are a mid-market CEO or COO, 95% of this news is irrelevant. You don't need to care about model benchmarks or GPU supply chains. You need to focus on context and connection.

What Doesn't Matter

Model benchmarks. The difference between 88% and 91% on a coding benchmark has zero correlation with whether a system can extract billing data from your invoices. Most modern models are more than capable of executing standard business logic.

What Actually Matters

Reliability and Fallbacks. What happens when the model returns an error? Designing robust fallback routines (e.g. routing the task to a human) is the difference between a system that runs forever and one that breaks on day two.

Operational Ownership. Do you own the code, or are you renting a SaaS dashboard that can raise prices next quarter? Build custom IP inside your repositories.