Forbes, August 28, 2026: an author argues to 'take humans OUT of the AI loop' — right about the bottleneck, aimed at a friction AppH never imposes
On August 28, 2026, Forbes published a piece by Joe McKendrick citing the author of the new book 'No One Works Here': keeping a human in the loop for decisions a machine could already make is now a competitive disadvantage, not a safeguard. His sharpest line — the human operator's hesitation, "the need to schedule a meeting, build consensus," "is not a safety feature, it's a bottleneck" — and his point that auditing an agent's output often takes longer than doing the work yourself, land on something real. AppH doesn't deny it. But the piece treats as one category what AppH's product has distinguished as two since its first module.
According to Joe McKendrick (Forbes, August 28, 2026), the piece draws on a recent book, "No One Works Here," whose author argues the era of "human in the loop" as a default safeguard is ending — not because the risk went away, but because the cost of caution has outgrown its value. The core argument: at every step where an organization inserts a human to approve what a machine could already decide alone, it pays in speed what it believes it's gaining in safety — and in a market where competitors automate without that friction, that "safety" becomes a measurable handicap. The piece's most quoted line is blunt: the human operator's hesitation — "the need to schedule a meeting, build consensus" — "is not a safety feature, it's a bottleneck." McKendrick goes further: carefully auditing an agent's output line by line often takes longer than just doing the task yourself, which drains the exercise of its practical value. The piece's conclusion calls for more AI autonomy in core business processes — but closes on a caveat that matters: guardrails and governance "at all times," not their removal.
AppH isn't going to strawman this argument to make it easier to dismiss — the bottleneck diagnosis is real, and a business that routes every micro-decision through a full meeting pays a speed cost no safety argument justifies. But the piece treats "a decision a machine could make" as one category, where AppH has drawn two since its first module. The overwhelming majority of operational decisions an AppH agent makes — triaging an inbound email, proposing a time slot, drafting a reply, filing an attachment, updating an internal status — never touch a human: that's exactly the autonomy the piece is calling for, and AppH already has it. The approval click exists only for a narrow, specific subset: an action with real consequence — money moving, a booking or order getting canceled, a message going out to an external customer, sensitive data changing hands. That's not "a human approves everything" — it's a human approves what's expensive to undo. And the piece's own conclusion closes on exactly that principle — guardrails and governance "at all times" — without saying what that looks like in an actual product. AppH doesn't have an abstract governance idea to sell: it's literally the approval click on consequential actions that already exists in every module.
For AppH
- McKendrick's diagnosis of the bottleneck created by blanket human validation is exactly the problem AppH solved upstream: by putting the approval click only on actions with real consequence, AppH already delivers the full autonomy the piece is asking for on the vast majority of operational decisions, without trading speed for safety on the ones that actually matter.
- The piece's closing caveat — guardrails and governance "at all times," not their removal — isn't a theoretical hedge at AppH: it's a product behavior already built and checkable, not a promise to fund later.
Against / the honest limit
- AppH's approval click is, by definition, still real friction — for a business that needs to send 200 quotes in an hour, waiting on a human to validate each action flagged as "consequential" costs time that McKendrick's thesis would fairly call a bottleneck at that specific volume.
- The line between "trivial operational decision" and "consequential action" isn't a law of physics — it's a configuration choice AppH makes with each client, and a reader persuaded by McKendrick could reasonably argue AppH still draws that line too cautiously on some actions a well-governed agent could already execute alone.
What sets this piece apart from others we've covered this month is that it doesn't say what we're used to hearing. It doesn't argue "keep a human in the loop, it's safer" — it argues the opposite, with real reasoning behind it, not a cheap provocation. We're not going to pretend McKendrick is wrong on the substance: an organization that schedules a meeting to approve what a well-built agent could already decide alone is genuinely losing a race it didn't have to lose. Where we differ isn't the principle, it's the scope. AppH never put a human in front of every decision — it put one in front of the ones where a mistake is expensive to undo: the money, the cancellation, the message that goes out to a customer, the sensitive data. Everything else already runs without one, exactly as this piece asks for. The real disagreement, if there is one, will eventually be about where to draw that line — not about whether to draw one.
Verified by a human at AppH