Nobody hires Kirkland & Ellis because they write good
Why build vs. buy is a false choice in professional services
tl;dr: the cheaper the memo gets, the more expensive the name on it becomes.
fast framework: price the apology, not the artifact: who has to show up when it breaks?
open question: if clients can sue the firm but not the model, is the entire industry just liability arbitrage with good branding?
A few weeks ago, the FT reported that Kirkland & Ellis, the largest law firm by revenue, was committing $500 million to build internal AI tooling. Firm chair Jon Ballis explained the logic plainly: off-the-shelf tools like Harvey are “raising the floor for everyone,” so any real edge has to come from something a rival can't simply license.
Like with all AI news, cue the “______ is cooked” takes. In the hotseat this time: Harvey.
And like many reactionary takes, it smuggles in a category error worth naming because it’s one I’ve been guilty of myself.
At one point in my life, I was a complete outsider to professional services. I marveled at the prospect of being one of those uber-smart young professionals cranking out that brilliant work product.
Generally, I thought:
BigLaw writes documents.
MBB consulting firms make slides.
BB+ investment banks build models and pitchbooks.
AI can write documents, make slides, and build models. Ipso facto, AI is coming for legal, consulting, and financial advisory.
AI will absolutely make the artifacts of professional services cheaper to produce. It will produce first drafts, diligence summaries, market maps, research memos, buyer lists, comp sets, board pages, redlines, operating-model slides, and first-pass recommendations.
But let’s take a step back. The same way Carvana isn’t really in the “selling cars” business, Kirkland isn’t in the “writing documents” biz. Carvana is a subprime auto loan origination machine with a cute vending machine gimmick. Kirkland is an authority broker & professional pointy-end-of-stick.
Clients do not hire Kirkland because they need a document. The document is just a delivery mechanism for “we mean business.”
The product is the message. The message is medium-agnostic.
Could be a fax. A candygram. A poem. If I was jockeying for position in a liquidation and I got a hand-quilled couplet on Kirkland & Ellis cowhide I might be more intimidated.
We signed the deal at midnight, left you out; Subordinated now, you'll do without.
But the message isn’t the words either.
Think about the same cowhide with the same couplet. Except this time it’s signed Kirklandt & Ellison. Everyone’s laughing. “We’ve got BigLaw at home” energy.
The words are just another medium. The message is who’s saying it.
People don’t hire these firms because they need brilliant memos. They hire these firms to convert work product into reliance. Into something they can act on: sign, disclose, reorganize, defend to a board, take to market, close.
The deliverable isn’t the service. It’s the residue. It’s the container. The thing that survives the meeting and goes into the data room. The thing journalists can obtain and Congress can subpoena.
The product is the moment a client is willing to act, under someone else's accountability. Memos and slides and CIMs are worthless as work product without the trust that converts it to revenue.
The Reliance Layer
So if they aren’t selling documents, what do they make?
Let’s call thing being sold the Reliance Layer: the institutional machine that turns work product (whether paralegal, word processor, or AI-assisted) into trusted action.
It’s a combination of firm knowledge, brand equity, regulatory insulation, lobbyist influence, and a shortlist of names who will end up holding the bag if/when shit goes down.
Every elite firm has one; they just brand it differently. I know because I sold it. In banking, we called it “unparalleled industry coverage” and “24x7 transaction execution support.” I’m sure BigLaw and MBB have equally irritating terminology. Same same, but different, but also kinda the same.
To uncomplicate this, let’s complicate it first. I think about professional services the way airlines think about themselves. An airline looks like it sells flights. It actually manages perishable inventory. The seat flies whether or not someone is in it, the plane costs the same either way, and a seat that takes off empty is revenue that never existed. So the metric that runs the business isn’t flights flown or tickets sold. It’s PRASM: passenger revenue per available seat mile. Yield per unit of capacity that expires on a schedule.
Professional services has the same shape. A firm looks like it sells documents. It actually manages perishable capacity: a partner-hour, a principal review slot, a senior-banker call. Each one converts to revenue or expires worthless, and you can’t warehouse Tuesday. So the metric that matters isn’t memos produced.
It’s the firm’s equivalent of PRASM: revenue per available unit of trusted expert capacity. The Reliance Layer is the airline. The scarce input is not artifact production. AI just made that nearly free.
The inventory is the layer itself: the supervised judgment that converts artifacts into something a client will rely on.
So the metric measures the layer, and the test that follows asks who owns it. For any AI bet in or around knowledge work, ask three questions:
Artifact or conversion? Does the position own the production of work product (commoditizing fast) or the Reliance Layer that converts it into trusted action (where the rent lives)?
Who captures the PRASM uplift? AI raises throughput per expert. Does the layer’s uplift accrue to the incumbent firm, to a vendor, or get competed away to clients? Strong demand plus a binding capacity constraint means the firm keeps it; weak demand and no way to redeploy saved labor means it leaks to price.
Where does accountability sit? Whoever signs, insures, and bears the liability owns the durable position. A model can generate legal text, but it can’t be admitted to the bar, lose a license, or take the board’s call when someone asks whether this is safe.
The closer a business sits to low-accountability artifact production, the more AI commoditizes it. The closer it sits to high-stakes reliance, the more valuable the layer becomes. And the more defensible. The layer is not a defense against AI. It’s the intake valve.
Recommended for you:
Perfect Is Easy. Imperfect Is Hard.
I feel like writing has really been under a microscope recently.
In law, “AI passed the bar” is the same category error in miniature. Passing the test is not the job. The job is entering an accountability system: admission, privilege, sanctions, malpractice exposure. BigLaw AI isn’t document generation; it’s yield management under liability.
In consulting, a generic tool can say “centralize procurement” or “exit the segment.” The partner knows whether this CFO can force the regions to comply, or whether this CEO has the board support to do it. By this client, at this moment. Most consulting value lives in that clause, and a model doesn’t have it. The production side is already moving. McKinsey’s internal assistant runs north of 500,000 prompts a month (roughly one every five seconds, around the clock). But adoption of the tool is not the same as capture of the value.
In M&A, a CIM is not an auction and a fairness deck is not board confidence. A dead deal, a busted process, a missed market window. That’s dead inventory, opportunity cost with nicer fonts. The bank’s scarce asset isn’t analyst hours; it’s the senior capacity to turn a live situation into a closed fee before the window shuts. The economics are lumpy. A handful of high-stakes mandates drive the year. That is exactly why senior judgment, not throughput, is the binding constraint, and why faster artifact production alone doesn’t move the number that matters.
A generic market summary is exposed; a live board recommendation is not. A first-pass contract summary is exposed; a negotiated risk allocation in a contested deal is not. In every case the artifact gets cheaper and the conversion gets more valuable.
Who owns the Reliance Layer is the investment question.
There are three answers, and each is a position.
Incumbents. If demand is strong and trusted capacity is the bottleneck, AI lets a firm push more high-value work through the same senior people. PRASM goes up and the firm keeps the spread. Kirkland’s $500 million isn’t a Harvey-replacement story; it’s a Harvey-absorption story. The bottleneck was never generating drafts. It’s the internal trust infrastructure that turns drafts into filings: routing, review, supervision, privilege, billing. Build that, and the firm can safely consume more vendor AI than any rival and convert more of what it consumes. They’re not trying to become Harvey. They’re trying to become Harvey’s biggest customer. More Harvey in, more Kirkland out. The levers are realization, write-offs, leverage, and the move toward value-based pricing where the work supports it.
Vendors. The tooling layer is real and growing fast. In banking, Rogo raised a $160 million Series D in 2026 at a $2 billion valuation; its agent, Felix, screens deals, drafts CIM sections, runs buyer outreach, and works through data-room diligence for more than 35,000 professionals at over 250 institutions, Lazard, Moelis, and Rothschild among them. The vendor risk isn’t that incumbents clone it. It’s abstraction: if the firm owns context, permissions, privilege, QA, routing, and sign-off, the vendor becomes one callable service inside the firm’s machine. The vendor wants to become the workflow; the firm wants to own the workflow. If Kirkland’s build works, Harvey sells more, not less. It just sells it as an ingredient. That fight is live and unsettled. (A major bank’s own growth-equity arm sits on Rogo’s cap table.)
Where do vendors win outright? In greenfield or low-accountability work with no incumbent Reliance Layer to defend, and in becoming the system of record. A vendor that owns the data and the workflow can starve the incumbent’s trust infrastructure from below (the bull case for the tooling layer). The Rogo client roster tells you which one is furthest along.
Clients insourcing. The cheaper artifacts get, the more work moves in-house. Real, but concentrated in exactly the low-accountability tasks the framework already flags as exposed.
None of this is a clean build-versus-buy choice, and treating it as one is its own mistake. The durable pattern is internal workflow plus external infrastructure: firms own the relationship, context, judgment, and sign-off; vendors supply models, data, and rails.
My view is that Kirkland will build a proprietary platform which will make it easier to keep licensing third-party tools. Their play is to own the path from artifact to action, not the tooling to get there.
So the sharper question for any position is not “build or buy” but “who ends up owning the Reliance Layer once the dust settles?”
The underwriting heuristic: run it at 10x
The cleanest stress test is to assume the models get ten times better. If a position only produces artifacts, 10x kills it. If it owns the Reliance Layer, 10x may strengthen it: more raw output flooding into the same scarce conversion capacity raises the value of whoever can route, supervise, and stand behind it.
The firm with the widest layer gets to has the most capacity to weather the storm. So underwrite the conversion layer, not the generation layer. The winners aren’t the firms or tools that generate the most output; they’re the ones that convert the most output into trusted action per scarce unit of capacity.
Pressure testing the Reliance Layer
The Reliance Layer isn’t magic. There are four real pressures on the thesis. Each comes with a mitigation, and the mitigations are not evenly distributed.
Pricing leak
The pressure: if AI just makes artifacts cheaper and demand is soft, clients won’t pay old fees for faster work and the uplift leaks to price. The shift toward value- and outcome-based pricing is the tell for who’s actually capturing the gain.
The mitigation: a pricing leak needs a forcing function. Medicine got outcome-based payment because doctors don’t control the payer. Lawyers control everything. The fee rules are written by lawyers, enforced by lawyers, and appealed to judges who are lawyers, in a country where lawyers are still the largest bloc in Congress and half the Senate.
The apprenticeship problem
The pressure: firms train senior judgment through junior artifact work. Strip out too much of it without redesigning training and you optimize this year’s margin by starving the judgment you sell in ten years.
The mitigation: a precedent pointing the other way. The last time the junior artifact got automated was the spreadsheet, and analysts barely existed before the spreadsheet. The analyst class didn’t shrink. It was born.
Vendors moving up
The pressure: a tool that quietly accumulates context, accountability workflow, and the client relationship stops being a component and starts becoming the firm.
The mitigation: As of right now, non-lawyers can’t own law firms in the US outside of a handful of states with pilot programs.
Demand elasticity
The pressure: the layer’s whole PRASM story assumes a binding capacity constraint. No constraint, no story. Just deflation.
The mitigation: the legal book hedges itself. Boom times, bust times, legal work still exists. The window doesn’t close as much as it rotates. It is not a coincidence that the firm on top of both cycles is the one spending the $500 million.
The mitigations rank the pillars. Consulting has no licensing wall. Banking answers to regulators who aren’t bankers, and its vendors are already inside. Law regulates itself, prices itself, and hedges itself. Which is why the anchor of this essay is a law firm (and an area we are very bullish on investing in).
What to take home
The question to ask of any AI play in knowledge work isn’t “can it make the deliverable?” Of course it can. It’s: who reviews it, owns it, prices it, and stands behind it when the recommendation becomes a contract, a filing, a board vote, or a closed deal?
The “Harvey is cooked” takes had it exactly backwards. Tools that raise the floor only threaten firms that compete at the floor. Kirkland isn’t spending $500 million to use less Harvey. It’s spending $500 million on the internal trust infrastructure that lets it safely consume more Harvey than anyone else: routed, reviewed, privileged, signed. Not the name under the document. The name under ten times the documents.
This was a great read!
Loved reading this!