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The AI boom feels a lot like the telecom bubble of the early 2000s — a race to build infrastructure faster than anyone can figure out how to monetize it. Investors like Michael Burry and industry insiders aren’t betting against AI itself; they’re betting against the unsustainable hype cycle surrounding it. Just like fiber-optic cable once outpaced demand, today’s AI valuations are outpacing real business value. The tech is real, the promise is real, but the process behind it

We see it everywhere. In school, a simple assignment becomes an epic because the deadline is far away. On Saturdays, three chores take all day. Fifteen chores before lunch, though, and suddenly we are a machine. Inside teams it looks the same. Years ago, we built monthly sales reports with clunky tools. Data dumps to Excel, formulas that would make a grown analyst cry, screenshots pasted into PowerPoint. It was slow, manual, and fragile. But we had a clear ritual. Billing fin

Rituals aren't the issue. It's rituals without results that matter. In this episode, we redesign stand-up meetings and status updates to drive work forward. Rotating facilitation highlights gaps, and a simple checklist for Mondays, Wednesdays, and Fridays helps maintain standards while fostering innovation. We frame each meeting as a two-party agreement between management and creators, and discuss the importance of recognition.

Forget the meme that “this meeting could’ve been an email.” The real fix is an acknowledgement cycle: tiny Looms, one change at a time, a weekly “did you do the thing?” scoreboard, and pull-based habits over notification spam. Transport information and confirm that it has become a shared understanding.

When Six Sigma meets slide decks, the math stops working. Manufacturing aims for three defects per million; knowledge work hides a million invisible defects behind one perfect presentation. In this episode of Process Debt, Chris and Toby unpack why “good enough” varies by context, how to decide which processes need rigor, and how novelty and personality often disguise systemic inconsistency. Not every task needs five sigma, but every team needs to know where precision actuall