Thursday, September 24, 2026

Who trains the next reviewer?

 

Who trains the next reviewer?

I had two conversations this week that I could not stop thinking about, and the annoying part is that neither person was trying to make a point. They were both just describing their own Tuesday.

The first was a senior accountant at a firm in Brooklyn. Senior accountant is a strange promotion. Nobody throws a party. What actually happens is that the difficult files start appearing on your desk, and one day you look up and realise you have stopped being the person who prepares the work and started being the person who checks somebody else's.

Those are not the same job. Preparing is procedural. Checking is diagnostic. You look at a finished reconciliation and you know, in about four seconds, roughly where the problem is going to be hiding. Nobody teaches you that. It shows up, or it does not.

The second was a man who runs offshore accounting teams for Western firms. He had been thinking about what happens when the machine assembles the file and a person signs it, and he said it better than I have managed to:

"The valuable version of my team is not the one that does reconciliation, it is the one trained to audit a prepared reconciliation fast and catch what is wrong in it. That is a different hiring and training problem than the one I have been solving for. Pods built for production do not automatically become pods built for verification."

He is right. And I have been sitting with it for two days because there is a second half he did not say and I did not think of until later.

The problem is not that the two skills are different.

The problem is how the second one has always been made.


You already know this. You have just never had to say it out loud.

Think about how you actually got good at review.

You did not read about it. There was no session on it. You built several hundred reconciliations, a healthy number of them were wrong, and somebody more senior sent one back with a single question and no other comment, which is somehow worse than being shouted at. And then you did it again. And somewhere in year three or four you started seeing the error before you found it.

That instinct is a residue. It is what is left over after enough repetitions of the boring work, done badly, then corrected in public.

The production years were not a toll you paid on the way to judgment. They were the machine that produced it.

Which brings me to the question I have not been able to answer.

If the machine does the first four hundred reconciliations, where does the fifth-year reviewer come from?

Your current seniors are fine. They already have it, they earned it the old way, and nobody can take it off them. The people who would have become your seniors in six years are the ones I would worry about, because they will not have had the six years. They will have had six years of checking work that was mostly right, which teaches you almost nothing, because the thing that teaches you is being wrong in front of somebody who noticed.


The comfortable answer is wrong and I want to say so before someone else does

The comfortable answer is that we keep juniors doing manual work in order to season them, like a cast iron pan.

That is a bad answer. It is also never going to happen. No firm is going to pay for deliberately slower work as a character-building exercise, and no junior is going to sit quietly through three years of data entry while the person at the next desk finishes at four.

The real answer is less tidy, and it is this. If the training used to be a by-product, it now has to be on purpose.

Somebody has to design it. Not buy a tool. Design a way for people to build the judgment that the grunt work used to hand them for free, in a world where the grunt work has left the building.

I do not have a finished answer to that, and I would be a bit suspicious of anyone who says they do eighteen months in. What I do have is the part that comes first, which is knowing what you are actually training.


The good news, and it is better than I expected

Here is where I changed my own mind this week.

Reviewing a junior and reviewing an agent turn out to be the same skill.

Both hand you work that looks finished. Both are confident. AI is wrong the way a very polite person is wrong: fluently, in a complete sentence, with excellent formatting. And both are right most of the time, which is exactly what makes the occasional miss dangerous, because you stop looking properly.

In both cases the question you are asking is identical. Not "is this wrong" but "where would wrong hide in this."

So if you have ever reviewed another person's work, you already have the beginning of it. You are much further along than you think, and considerably further along than somebody who is brilliant with the tools and has never once had to sign their name underneath numbers they did not prepare.

That is the whole reason our training is built around judgment rather than tooling. Not because the tooling is unimportant, but because the tooling changes every few months and the judgment does not. AI does the typing. You make the judgment calls.

And it is why the hardest belt is not the one where you build something clever. It is the one where you decide what not to automate, and where to stop trusting what comes back.


The same problem, from two different chairs

If you work on the books, this is a career question, and the honest version is uncomfortable. The part of your work that is easiest to hand over is the part you are currently fastest at. The part that is hardest to hand over is the part you probably undersell, because it feels like something anybody could do. It is not. I promise you it is not.

If you run a company, this is not a career question at all. It is a workforce design problem on a very long fuse.

You will get the productivity. That part is real and it shows up fast. What shows up slowly, and only if somebody builds it deliberately, is the bench underneath your current senior people. Nobody notices a broken training pipeline in year one. You notice it in year five, when the person who should have been ready is not, and you cannot make up the ground quickly because the ground was made of repetitions that do not exist any more.

The firms that come through this well will not be the ones with the best tools. They will be the ones who worked out early how to make reviewers on purpose.


Both doors are open and both are free

If you work on books, the nine-belt AI Native Foundations course is free for life. It normally costs $1,000 per person. Twenty-seven worked examples built on the real work rather than a case study, and the belts that matter most for everything above are the ones about judgment and knowing when to stop trusting the output.

And you can gift that same course, free for life, to every client you have. Uncapped. Not a trial and not a discount code. Your clients are one rung down the same ladder, and it is a reason to be in touch that is not an invoice.

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If you run a company with ten or more employees, the entire first year of the $25,000 programme is free. All nine courses, a complete AI-Native Company Transformation Plan, monthly CEO peer-group forums, and Foundations training for every employee you have.

That last part is the one that matters here. Training everybody in the building is how you rebuild the bench on purpose rather than hoping it happens by accident. Ten employees is a real threshold rather than a suggestion, and year two is $25,000. Sign up free first, then request CEO access from the offer bar inside your account.

https://humansplusagents.ai/legacy-sbc-aia

Nothing expires. No card. Nothing renews.


We are all working this out at the same time, and the people who will figure it out first are the ones already doing the work rather than reading about it. If you have a view on where the next generation of reviewers comes from, I would honestly like to hear it. I am still short of an answer.

The community is free and this is mostly what we talk about: https://www.facebook.com/groups/1024923770013348

And if you would rather start with something small, we build free agents one job at a time, yours to keep, no course required first: https://aiaccounting.legacysbc.com/claim-agent

1 comment:

  1. Increasingly, I wonder if we are seeing a greater separation between folks who executors and folks who are auditors. There are lots of different semantics available to parse these categories into different descriptors: producers/verifiers, builders/reviewers, juniors/seniors, worker bees/manger bees, but at the heart of each of these pairs is the idea that some people gravitate towards executing tasks, typically pre-defined, and capable of producing lots of great, profitable results. And other people gravitate towards picking apart the SOPs; looking for ways to understand, to improve, to advance, or to make easier. In the years I worked in Internal Audit, this mindset, one of looking for flaws in order to improve the greater whole, was one that was cultivated and supported. In the day to day grind of corporate business… not always so much.

    I believe AI is changing the dynamic here, again. Generative AI easily fits into the workhorse slot, executing defined and well controlled processes with unmatched (by humans) speed and efficiency. This is changing the way humans have to think of their jobs; human intervention is still important, as a gatekeeper on both ends of the processing by AI, and to interpret and parse the process (essentially, to make sense of the input and output from these processes). But this require more of an audit mindset, not an executor mindset. Companies don’t need as many worker bees, and as time goes on, may replace them entirely with automated AI processes configured to do the day to day SOP work.

    This is forcing more and more of us to become comfortable with the auditor mindset: the idea that we should be examining the results of our financial processes and learn how to spot things that don’t make sense or things that may be a red flag of forthcoming anomaly. As discussed recently in the Blog Post by BON, “Who Trains the Next Reviewer?” (https://followbonsplace.blogspot.com/2026/09/who-trains-next-reviewer.html?lr=1790927849611), this facilitates a training conundrum: Who will train the next set of reviewers when the reviewing skillset has historically been developed by producing? It’s a timely and appropriate question. But it’s one that may have a complex answer. It may be that some of the answer lies in having new employees work with or shadowing AI, and learning how the actual process is executed. The answer may also include new and adaptive teaching tools, ones that require a reasoned breakdown of the process and hands on expertise to put it back together. Or the answer may include new and novel ways to grow the collaboration between reviewers/auditors/verifiers.

    The take away from this for me is that we need to support and encourage activities that bring folks together who are on the endpoints of AI execution. In addition to consideration for accuracy, cost, expediency/ROI, and a myriad of other performance metrics, AI implementation should also consider the way it impacts the ongoing educational needs of staff and management. Training should be more aware of how processes require a reviewer mindset. The desire to examine operations and inspect its component parts doesn’t natively live in everyone, but it can be cultivated. This process not only sets our current processes up for success, it prepares the next wave of folks we will want to call when future processes fail.

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