Business Unusual

How should AI agents handle failures in critical processes?

Even the smartest AI agents fail. This post explores how to design agents that can handle failure in critical processes — without crashing the entire system.

What happens when AI eliminates "unscalable" business advantages?

If your brand’s “magic” can now be faked by AI, was it ever magic—or just polished friction no one questioned? Welcome to the culture reckoning.

How do you reskill a team around AI workflows without losing velocity?

AI isn’t making your team smarter—it’s just making their outputs faster. Guess what’s quietly vanishing? Original thought.

What is a realistic approach to AI audit trails in small teams?

Most small teams don’t need better AI tools — they need better memory. If your audit trail is vibes and Slack threads, read this.

How do AI copilots change middle management forever?

AI didn’t kill middle management. It just revealed how many were never really managing—let alone leading—in the first place.

Why every letting platform should think like a neobank. Onboarding, retention, embedded finance — not listings — are the real product.

If letting platforms think the listing is the product, they’ve already lost. It’s not a transaction—it’s a multi-year financial relationship.

Build-to-Rent, meet Built-to-Automate. BTR has the structure for automation — predictable units, central ops, clean data — it just needs the mindset.

If you're still throwing people at problems in Build-to-Rent, you're not scaling—you’re babysitting. The real play? Treat ops like code.

Can you trust the output of a model you can't fine-tune or self-host?

You wouldn’t let an intern rewrite your product roadmap—but you’re trusting black-box AI to steer your business? Might want a second look.

Is local inference worth the trade-off in trust and privacy?

Running AI locally sounds like a privacy win—until you realize you’ve just traded one black box for another. Who’s really in control here?

When two models disagree — who decides?

Two AI models. One decision. And they both swear they’re right. When the black boxes bicker, who breaks the tie—and how?