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That Email Should’ve Been a Meeting
We joke that “this meeting could’ve been an email,” but Charlie Munger would flip that logic on its head. In most organizations, the real failure mode isn’t too many meetings — it’s hiding work inside emails no one ever truly acknowledges. A good meeting, with a shared agenda and a visible workflow, creates something email never can: confirmation, context, and community. Reduce your emails by having better meetings. That’s how you start paying down process debt.
Chris Terrell
Dec 26, 20253 min read


The Process of Blame: Why Fast Thinking Breaks Slow Systems
Blame is the fastest reflex in business. A quick way to dodge discomfort without fixing anything. But real process health comes from slowing down, understanding the work, and building boring-but-powerful rituals that prevent chaos. When we value clarity over reaction, the fires stop before they start.
Chris Terrell
Dec 19, 20253 min read


AI, Process Debt, and the Myth of Rosie the Robot
Lately, when people talk about AI, I think they believe they are buying Rosie. But we are not building Rosie. Not yet. And chasing Rosie too early is how you quietly pile up a whole new layer of process debt. AI is not doing your dishes In the real world, the direction of AI right now is information, not activity. It can summarize meetings, draft emails, write status updates, brainstorm project plans. It can churn through data at a scale that used to require an army of analys
Chris Terrell
Dec 12, 20253 min read


When Simple Collaboration Becomes a 20-Minute Detour
Collaboration in the modern workplace frequently falters before actual work starts. This week’s Process Debt story highlights how a simple profile update request turned into a 20-minute ordeal of password resets and confusion. It demonstrates how invisible process friction can disrupt even the simplest tasks, not due to individual failure, but because our systems impose unnecessary obstacles.
Chris Terrell
Dec 5, 20253 min read


The Ones, the Zeros, and the Humans Stuck in the Middle
AI can generate anything, but it can’t deliver the one thing computers depend on: predictable abstraction. Unlike ones and zeros, LLMs guess — which means humans still end up in the middle, fixing the gaps and cleaning up the process debt that follows.
Chris Terrell
Nov 28, 20253 min read
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