I spent a year routing every product decision through token budgets and latency targets. The rule was simple: if an AI could generate the draft, the spec, or the volunteer script in under four seconds, we shipped it. What I missed was the moment the curriculum stopped matching what a real 7-minute volunteer could actually finish on a Tuesday night with a stack of printed pages in front of them.
The cost showed up in completion rates. We had higher output and lower retention. The volunteers kept opening the materials once, getting stuck on the third activity, and printing something else instead. I kept measuring the wrong thing because the model made it easy to keep measuring the same thing.
Charlie Munger’s latticework of mental models insists that a single lens will always blind you to what the model cannot see. I had treated speed and token cost as the only two models that mattered. Presence was not in the lattice at all.
The routing habit that trained out my own judgment
Every ticket went through the same path. First the model wrote the acceptance criteria, then it suggested the flow, then it generated the test cases. I reviewed the output for factual errors and moved on. The loop felt disciplined until I noticed I was no longer asking whether the volunteer would still be standing at the table when the third page asked them to cut out six small crosses.
The habit removed friction, but it also removed the friction that forces judgment. When the model cannot see the table, the scissors, or the child who needs the activity finished before the parents arrive, the only remaining signal is whether the tokens stayed under budget. That signal is too narrow for ministry work.
After six months the pattern was clear. Features that scored highest on our internal efficiency dashboard were the same ones that generated the most Monday-morning support tickets from volunteers who could not finish the lesson.
Presence as the override at the print step
The print step is where the abstract workflow becomes physical. I started showing up at two different churches during the hour when volunteers actually assembled the materials. One Tuesday I watched a leader try to follow a three-column layout on an 8.5-by-11 sheet that had already been folded twice. The model had optimized the layout for screen reading. The volunteer had no screen.
That single observation overturned three accepted stories we had shipped in the previous quarter. The fix was not another prompt. It was adding a hard stop: no layout change could ship until someone had printed it on the exact paper stock the volunteer would use and completed the activity with a stopwatch running.
The latticework requires multiple models to stay in tension. Token cost and completion time under real conditions cannot be collapsed into one number. When they conflict, the print step wins because that is where the actual work happens.
How emotional intelligence shows up in a sprint review
Sprint reviews used to be a slide deck of velocity and error rates. After the print-step visits I changed the format. The last ten minutes became a short video of a volunteer attempting the new flow while thinking out loud. No narration, no cuts. The team watched the pauses, the page flips, the quiet “this doesn’t make sense” that never appeared in the analytics.
The first time we ran the video, two planned features were removed before the next sprint began. Not because the metrics said they were slow, but because the volunteer’s frustration was audible. That data had always existed; we had simply routed around the channel that carried it.
Emotional intelligence in this setting is not a soft skill layered on top of product work. It is the additional mental model that tells you when the existing metrics have stopped tracking the outcome that actually matters to the volunteer. Without it the lattice stays incomplete.
Your Turn: Apply This Today
- Pick one live ministry workflow that touches volunteers this week and block fifteen minutes on your calendar to watch it in person without a laptop open.
- Print the exact materials the volunteer will use on the same paper they receive and complete the full activity yourself with a timer running.
- Write down the single moment where the workflow required a judgment the current model cannot see, then log that exact moment in the ticket system as a required check.
- In the next sprint review, replace one metrics slide with a two-minute unedited clip of a real user attempting the task and end the meeting without discussion.
- Remove one previously accepted efficiency target that no longer matches what you observed during the print step and document the removal in the same place you track token savings.
- Schedule the same fifteen-minute presence audit on the same workflow for next week and record only the one adjustment you made because you were physically there.
The Morning the Print Step Broke and The Inner Skills I Let the Model Train Out of Me both trace the same gap between what the model optimizes and what the volunteer actually experiences.
I consult with product leaders and ministry teams on presence audits, sprint-review redesign, and workflow overrides that protect volunteer completion. Let’s talk.