AI is supposed to save time. So why does so much of that time seem to disappear?
In this episode, Gabe and Kelly dig into Glean’s 2026 Work AI Index and two terms that capture a growing problem at work: bot sitting—the human effort required to feed, monitor, correct, and clean up after AI—and botshitting—sending AI-generated work downstream without really understanding or validating it.
That leads to a bigger Organizational Gravity question: what if AI is making work faster without actually making the system lighter?
We talk about where those supposed productivity gains go, why human review is different from babysitting a poorly designed bot, and how unverified AI output can move risk downstream faster than the old process ever could.
The conversation also puts pressure on Organizational Gravity itself. I have often treated friction as evidence of unnecessary organizational weight, but AI exposes an important exception: some friction is doing real work. Verification, judgment, accountability, experience, and safety can all slow a process down for good reasons.
The goal cannot be zero friction. It has to be the right friction, scaled to the consequence of getting something wrong.
In this episode
00:00 — Bot sitting and botshittingWhat the terms mean and why individual AI productivity does not always translate into better organizational performance.
04:25 — Who botshits more?A funny statistic about men and women turns into a more serious conversation about confidence, scrutiny, and how people review their work.
07:35 — Human in the loop or babysitting the bot?Where useful supervision ends and poor system design begins.
09:05 — Why are people shipping work they cannot defend?Deadline pressure, trust in the technology, weak review practices, and the widening technology gap.
17:11 — The Gravity AuditBot sitting starts to look a lot like Human Middleware. Are we adding AI without removing the process that created the work in the first place?
25:00 — The 4:30 PM testThe deadline is real, you are tired, and AI gave you something usable. Do you ship it or tell people you will be late?
27:34 — Where is Gabe wrong?We put Organizational Gravity itself under pressure.
28:29 — Not all friction is badRemoving every manual check can also remove the judgment that keeps bad information from moving downstream.
33:41 — Zero friction is the wrong targetGovernance should create the right amount of friction based on the consequences of the decision.
37:00 — A revised rule for frictionRemove friction caused by poor design. Preserve friction that creates judgment, accountability, or safety—and periodically prove that it still does.
40:34 — Three questions before you automateWhat should actually disappear? What judgment still belongs to a person? How will we know the whole process got better?
The takeaway
AI can make work move faster while Organizational Gravity continues accumulating underneath it.
If humans are constantly feeding the bot, checking whether the bot is functioning, repairing bad output, and carrying knowledge that never made it into the system, we have not necessarily removed the weight.
We may have just compressed it and accelerated it.
The better question may not be:
How much work can we automate?
It may be:
What should become easier, and what do humans still need to struggle with long enough to understand?
And that leaves us with a question for the next episode: maybe Human Middleware should not disappear entirely.
Maybe the real question is:
What should humans still be in the middle of?
Source: Glean Work AI Institute, The Work AI Index 2026: Botsitting, botshitting, and the hidden human labor of AI at work (2026)
