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In conversationIvan Palomino hosts The Growth Hacking Culture Podcast. This conversation was published on 2026-09-29. What was said is below in Ivan’s questions and the answers to them, with every quotation checked word for word against the recording’s transcript. The transcript itself is not published here, and the reason is at the foot of the page.
Written from the transcript below and from nothing else.
Ivan Palomino opens on the arithmetic every AI productivity case rests on: cut a research team from ten to two, and nobody notices that half the questions stopped being asked. Rahim's answer is that the loss is not output, it is judgement, and that it accumulates the way debt does rather than arriving as an event.
The conversation turns on a distinction Rahim says he arrived at slowly and not in one moment. A senior leader makes a call. The recommendation underneath it came from a machine. Nobody in the chain did anything wrong, and nobody can now say whose judgement the decision was. That blur is what he means when he says AI is coming for your judgement rather than for your job.
The practical half is a framework Rahim says is not in the book. Humans in the loop is a start and it is too vague to act on, so he splits it: humans at the start, before the problem goes to the machine, and humans at the end, where somebody decides whether they would defend the thing in front of a court. He works on paper first, then asks the machine what he missed.
Ivan presses on whether this is learnable in the way a university course is learnable. Rahim says it is not, and that the book went through eleven or more drafts and a hundred readers telling him version seven was rubbish before it worked, which is the same iteration he is asking of a reader.
Spoken on the day and quoted as spoken. Where a line rests on something this research has checked, the research page is linked beside it.
“A lot of people talk about humans in the loop, and they say you have got to have a human in the loop when you are doing this decision. That is a first start, but I think we need to be a little bit more specific. We need to have humans at the start.”
Rahim Hirji on The Growth Hacking Culture Podcast. The evidence is on /research/human-in-the-loop-is-not-a-safeguard.
“Do you hand on heart know that that is the right decision to be made, and would you be able to defend it?”
Rahim Hirji on The Growth Hacking Culture Podcast. The evidence is on /research/what-is-judgement.
“What is happening is people are outsourcing their curiosity to the machine.”
Rahim Hirji on The Growth Hacking Culture Podcast. The evidence is on /research/superskill-curiosity.
“Do that first and then you can go to the machine and say, okay, what have I missed, or ask me questions, and it uses your brain to feed into its solution.”
Rahim Hirji on The Growth Hacking Culture Podcast. The evidence is on /research/human-at-the-start.
“So it is drift versus design. You do not want to be a drifter, you want to be a designer.”
Rahim Hirji on The Growth Hacking Culture Podcast. The evidence is on /research/design-versus-drift.
“The recommendation may have come from a machine. So where does that judgement come in? It becomes a little bit of a blur.”
Rahim Hirji on The Growth Hacking Culture Podcast. The evidence is on /research/capability-debt.
Ivan’s questions and the answers given, shortened and not rewritten.
It evolved over time, it was not one moment. I had seen it in organisations, and then I saw it in myself. I put a report together using one of these tools and I looked at it and thought, I have not done anything here. I did not put that together. And there were some hallucinations in it. That is when I drew a line.
It is the accumulated cost of the decisions you are not making, and the learning you are not doing, because the machine went past it. Like any other debt it is invisible, it runs in the background, and there is interest on it. The further you go, the harder it is to come back, because the team never did the reps.
Because it says nothing about where. We need humans at the start, so you do your own thinking before you go to the machine, and humans at the end, which is the point where you decide whether you would put your name to it.
Do the thinking on paper first. Work out what the problem set is, what you think, draw the diagrams. Then go to the machine and ask what you missed, or ask it to ask you questions. That way it uses your brain to feed its answer rather than the other way round.
It will not be a dashboard or an adoption metric. It is whether people are asking who decided this, and why. Not as a box to fill in, but as a question that has become inherent in how they look at things.
The other conversations on this site carry the whole thing as text. This one does not, and the reason is worth stating.
The only transcript available for this episode is the automatic one, which mishears names, infers sentence boundaries and supplies no punctuation. It can be cleaned into something readable, and what comes out is a reconstruction rather than a record. Publishing it as the conversation would be a claim this site is not in a position to make. The quotations above are checked word for word against it before this page is built; they are quoted because they survive that check. For the rest, go to the episode and hear it said.
Published here 2026-09-27. The episode was published by Growth Hacking Culture on 2026-09-29. Anything said in a conversation is speech, dated and attributed, and is not restated as a claim anywhere else on this site. Keynotes · Advisory · Boards