A few months back I spent time with some young lawyers, a couple of years out of school, working at firms whose names you would know. They were good. They were paid well. And they were trying to decide whether to leave.
The reasons came out the way they always do. The hours. The weekends that disappear. A life bent around a billing clock. But the longer they talked, the clearer it got that the hours were the symptom, not the disease.
What actually bothered them was harder to name. Nobody was teaching them anything. They were doing the work, mountains of it, and learning almost nothing about how to be the thing they had signed up to become. The early years were not a training program. They were a test of who would endure.
Let me tell you why that should worry the firms more than it worries the associates.
The grunt work was the classroom
Everyone treats the junior years as the price of admission. You do the research nobody senior wants to do. You read the documents. You write the first draft that gets torn apart. You bill it, the client pays for it, and you tell yourself it is dues.
But that grunt work was never only dues. It was the classroom.
You learned the trade by doing the rote version of it, over and over, next to someone who already had it. You saw how a good partner framed a question, what they worried about, where they looked first. The skill transferred sideways, by proximity, while your hands were busy on the boring part.
The apprenticeship was real. It was just a byproduct. No one designed it. It happened because the work and the people who knew how to do it were in the same room.
And it ran on luck
I learned this in a place that took development seriously. My years at McKinsey spoiled me.
The firm spent real money teaching people at every level, and the skill/will matrix I have written about before, the one that tells a manager whether someone needs a new skill or a new reason to care, I learned in that training, not on the job. And one of the firm’s own, a McKinsey partner named Max Landsberg, wrote the whole thing down in a book.[1] So this was a place that both taught the tool and produced the man who codified it.
I lucked into mentors who saw teaching as part of the work. I also watched good colleagues draw partners who saw it as a tax on their time. Even there, in the firm most famous for growing talent, who developed you was an accident of which engagement you landed on.
That was my time there, and I have no idea how much it has changed as the business grew and changed shape. But the lesson held even at the top of the trade: development was rationed by chance.
And chance is expensive. The associates who left were not only the ones who hated the hours. Some of the sharpest left in good part because the system never reached them. The professions even have a name for the filter: up or out.
Survival of the fittest sounds like a filter for the best. It is not. It selects for the people who will tolerate the conditions, which is a different group, and a smaller one.
The firm called the departures attrition. A lot of it was talent walking out the door before anyone had bothered to grow it.
The people in charge are not the villains
It would be easy to blame the partners. That is the wrong target. The problem is structural, and it shows up in two flavors.
In most of these fields, the people in charge were never trained to manage.
A partner is an expert in law, a lead is an expert in code, and the education that got them there taught the trade and said almost nothing about growing a person. The tool for it is not even exotic. The idea of matching how you manage someone to their skill and their will has been in the leadership curriculum for half a century, since Hersey and Blanchard.[2] But you do not meet it in law school or a computer science degree, and the managers who did pass through business school mostly met it as a slide in one intro course, not a habit they built.
But here is the part that shows it was never only about knowledge. At a firm like the McKinsey of my day, the tool was handed out and practiced. Partners sat through the same training I did. And some of them still did not develop anyone, because billings and advancement were what the firm counted, and growing people was not.
Training is necessary. It is nowhere near sufficient. Put the matrix in a partner’s hands and reward them only for revenue, and you have built a person who knows exactly how to develop talent and has no reason to.
There is a quiet irony in that. In the matrix as I learned it, the person who can do something but will not is a Blocker, high skill, low will. The partners who refuse to develop the next generation are Blockers on the one task that builds the firm’s future. They have the skill. Nothing rewards the will. So the damage builds. A partner who was never developed has no model for developing anyone, and passes the gap down to the people he is supposed to raise.
The classroom and the teacher, both gone
The accidental apprenticeship needed two things to work: the grunt work to learn from, and the proximity to learn by. Both are being pulled out from under it at the same moment.
Artificial intelligence is taking the grunt work. The mechanical research, the document review, the first draft, the exact tasks the junior learned the trade by grinding through, are exactly what the model now does in seconds.[3]
Remote and hybrid work is taking the proximity. The overheard call, the quick correction, the senior glance at a screen, the channel the rest of the learning traveled through, does not survive a calendar of video meetings.[4][5]
This is not only a law firm story. It is the same shape in software engineering, where the model now writes the routine code a junior used to cut their teeth on,[6] and across most of management, where the entry rung was always where judgment got built. The classroom and the teacher are both being removed, and few are treating it as a loss, because on a spreadsheet it reads as savings.
The question the spreadsheet never asks
Firms are starting to thin the junior ranks and calling it efficiency. Be careful with the causes. AI gets named in these cuts, and some of the thinning is old-fashioned over-hiring being corrected under a fashionable banner.
Some of each is likely true, and the distinction changes nothing here. The classroom closes either way. The logic is simple. The model does the junior work cheaper, so you need fewer juniors. On this year’s budget it is obviously right.
But the juniors were never only cheap labor. They were partners in training.
The grunt work was the tuition they paid in to learn the trade. Cut the training ground and you have not trimmed a cost. You have stopped manufacturing the thing the firm actually sells, which is judgment, the senior judgment clients pay a premium for and machines cannot yet supply.
I made the longer case in a recent piece: the prompt missing from every replace-the-consultants list is the one that asks whether any of the output is wrong, and the checking still has to be human. This is where the checkers were supposed to come from. The bill for that does not arrive this year. It arrives in a decade, when the bench that should be full of partners is thin, and the firm cannot work out where its seniors went.
You might expect the market to sort this out. A shortage of seniors should push firms to train more. But the firm that trains is not the firm that keeps the result. Grow an associate into a star and a competitor can hire her away the day she becomes one. Cheaper to let someone else do the raising and poach what they grew. So everyone waits for everyone else, the training no single firm is rewarded for doing stops getting done, and the shortage builds while each firm keeps making the choice that makes sense for itself.
So here is the question the efficiency case never asks. Who becomes the next partner?
The fix is not to protect the grunt work
The answer is not to make juniors keep doing the rote work a machine does better. That is nostalgia, and it loses.
The answer is to stop pretending apprenticeship is automatic, and design the thing that used to happen by accident. This is not a fantasy. Medicine did exactly that on purpose. A residency is a designed apprenticeship, not an accident of which supervising doctor you happened to draw.
Start with incentives. Training closes the knowledge gap for the firms that never taught the tool. But a tool no one is rewarded for using stays in the drawer, which is how the firms that did teach it still failed. Make developing people count toward partnership the way revenue does. A partner who builds three associates into stars should advance on that, not despite it. As long as the only scoreboard is the book of business, the matrix sits in the drawer no matter how many people you train.
Then use the machine as the teacher instead of only the replacement. If the model does the grunt research, the junior can spend that time on the judgment the research used to bury, under a senior who reviews the call. Done deliberately, AI lets a junior practice judgment years earlier than the old grind allowed. Done lazily, it just deletes the junior.
And aim the effort where it pays. The development worth doing is for the willing disciples, the ones with the will and not yet the skill, because those are the people who become stars. Not the resisters. The old system at least stumbled into a few of them. A designed one would find the talent the accident always missed, the people who never drew the right partner, never tested into the right room, and were filtered out before anyone saw what they had.
None of this is exotic. Some firms knew how to do it once and let it erode as they grew and chased scale. The surprising part is how few are doing it now, at the exact moment the old accident is breaking down.
The fight over working from home and the fight over AI both get framed as questions of cost and headcount. They are bigger than that. Judgment is the moat, but judgment is built, slowly, by people standing close to other people who already have it. We are quietly tearing down the workshop. And the people holding the saw are not asking who is supposed to come out of it.
Reference Sources
- Landsberg, Max. The Tao of Coaching: Boost Your Effectiveness at Work by Inspiring and Developing Those Around You. HarperCollins, 1996 (Profile Books edition 2003). The source of the skill/will matrix, a practitioner refinement of Hersey and Blanchard’s situational leadership, developed from Landsberg’s years as a McKinsey partner. The quadrant names used in this essay, Blocker and willing disciple, are the author’s working labels from his training and an earlier essay. Landsberg’s published labels name the coaching responses, Direct, Guide, Excite, and Delegate.
- Hersey, Paul, and Ken Blanchard. Management of Organizational Behavior. Prentice Hall, 1969 and later editions. The situational leadership model, matching a manager’s style to a person’s ability and willingness, that underlies the skill/will matrix and has been a staple of leadership curricula for decades.
- “AI Threatens Big Law’s Talent Pipeline.” Axios, 2 May 2026. Accessed June 26, 2026. On AI absorbing the document review, research, and first-draft work junior associates were hired to do, and the pressure that puts on the large junior-class model.
- Emanuel, Natalia, and Emma Harrington. “Working Remotely? Selection, Treatment, and the Market for Remote Work.” American Economic Journal: Applied Economics, vol. 16, no. 4, 2024, pp. 528-559. Accessed June 26, 2026. In a Fortune 500 call center, remote work degraded output quality and lowered promotion rates, with the largest effects on inexperienced workers.
- Emanuel, Natalia, Emma Harrington, and Amanda Pallais. “The Power of Proximity to Coworkers.” NBER Working Paper 31880, 2023. Accessed June 26, 2026. Software engineers at a Fortune 500 firm who sat near teammates received more feedback, concentrated in feedback given by senior engineers to junior ones.
- Brynjolfsson, Erik, Bharat Chandar, and Ruyu Chen. “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence.” Stanford Digital Economy Lab, 2025. Accessed June 26, 2026. Employment for workers aged 22 to 25 in the most AI-exposed jobs, software engineering among them, has fallen sharply since late 2022.