Vertical AI moats live in workflow frequency
Harvey reportedly added $100M net-new ARR in one quarter — but durability is predicted by the engagement ratio underneath. In vertical AI, the moat is how often the work returns, and what accumulates when it does.
An analysis of Harvey landed this week pairing two numbers that usually don't travel together: roughly $100 million in net-new ARR added in Q2 alone, and a reported 53% DAU-to-MAU ratio — with an $11 billion valuation on top. The figures are company-reported and the analysis is paywalled, so hold them loosely. But the pairing is the story, and it teaches something the revenue headline alone cannot.
A few weeks ago I argued that Cursor's spectacular ARR curve proves demand, not defensibility — revenue velocity is a measure of pull. Harvey's quarter invites the same discipline, and then rewards it differently, because the second number is a different kind of evidence. Revenue tells you customers bought. An engagement ratio above 50% tells you the product has become part of how the work is done, most days, for most of the people who have it. Those are different facts, and only one of them compounds.
Why frequency is the moat in vertical AI
In horizontal AI, differentiation keeps collapsing toward the models, and the models are rented — that was the Cursor argument. Vertical AI has an escape hatch, and it runs through frequency. Consider what daily use inside one profession's workflow actually produces.
Feedback velocity. A product touched daily by 142,000 lawyers learns about its failures at a rate a weekly-use competitor cannot match — every mis-drafted clause surfaces within hours, and the fix ships against live, domain-specific signal. The quality gap this compounds into is invisible in any demo.
Accumulated context. Daily use inside legal matters means the product increasingly holds the matter — documents, drafting history, positions taken, precedent preferred. That context is generated by use, is proprietary by construction, and makes the next task easier in a way no rival can cold-start. This is the vertical version of the semantic-layer argument: the data the workflow deposits is the asset.
Switching cost with teeth. Leaving an occasionally-used assistant costs a login. Leaving a system that holds your matter context, your templates, and your associates' daily habits costs retraining, migration, and a quarter of partner grumbling — real friction, the kind procurement remembers.
rendering diagram…
None of this says the ARR is fake — category urgency and large initial contracts are real forces, and legal AI has both in abundance right now. It says the ARR is the lagging indicator. The 53% ratio, if it holds, is the leading one: it is what makes this quarter's revenue likely to still be there, larger, in six quarters. A fast quarter can be bought with sales muscle and timing; a daily habit across a hundred and forty thousand practitioners cannot, and that asymmetry is the whole reason the two numbers deserve different weights.
The diligence question that separates lookalike vendors
At work, the conversation where this matters is rarely about Harvey itself. It is the enterprise AI lead comparing three vertical vendors whose demos look identical — same model underneath, similar UI, comparable feature lists — and whose contracts differ by multiples. The tiebreaker question I now put on the table: which recurring decisions does this product own?
Not "what can it do" — everything can do everything in a demo. Which decisions, made how often, by which roles, now happen inside the product? A contract-review tool that owns the first-pass markup on every inbound agreement is a daily habit with accumulating context. A tool that gets consulted when someone remembers it exists is a feature subscription with a renewal risk. The vendors know their own DAU/MAU cold; make them share it, by cohort, for accounts a year old. Reference calls should ask one thing above all: walk me through yesterday — not the rollout story, yesterday specifically. If the product doesn't appear in yesterday, it will not appear in the renewal.
The same lens applies to builders. If you are building vertical AI, the strategy question is not which model or how many features — it is which recurring workflow you can own end-to-end, at the highest natural frequency the profession offers. Own the daily thing badly rather than the quarterly thing brilliantly; the daily thing gives you the feedback loop to become brilliant, and the quarterly thing never will. Pick the workflow first; the feature list is downstream.
Steal this
For buyers: add two lines to vertical-AI diligence — vendor DAU/MAU by account cohort, and a written answer to "which recurring decisions does the product own?" Weight them above the growth slide, because they predict what the growth slide will look like in two years.
For builders: instrument your own frequency honestly, weekly, from launch. If your users' return rate is drifting down while your ARR is climbing — big contracts, low usage — you are renting category urgency, and the bill arrives at renewal. Frequency first, revenue follows; the reverse ordering has a short shelf life.
In vertical AI, revenue is what the moat pays out — the moat itself is the worn staircase: the same feet, every day, cutting grooves no competitor can copy.
