Chegg lost roughly 99% of its value after free AI arrived to do what students had been paying it for. Quentic sold compliance software — the kind of business a glance dismisses as commodity SaaS — and the same wave barely touched it.
The difference isn't luck. It's structure: four layers, each one a reason the customer still has to buy rather than build it or do without it.
Chegg: General answers, free elsewhere
This layer is worth something only when the knowledge is proprietary and maintained against a moving target. Chegg's answers were general and static: exactly what a language model now generates for free.
Quentic: Regulation encoded, and kept current
To use an AI's answer safely you have to be able to tell whether it's both correct and complete. In a specialist domain the customer usually can't. And if they could, they wouldn't have needed to ask. Picture an industrial site near Paris storing a given quantity of hazardous chemicals: an AI produces a confident recommendation in seconds, but the operator has to be certain it's compliant with both the EU Seveso III Directive and the relevant French rules, and typically has no way to verify that. Quentic's durability was never "knowing EHS" — it was the regulatory logic encoded into workflows and kept current across jurisdictions. Whether that ran on Java or PHP was irrelevant.
Chegg: Nothing to stand behind
No liability anyone needed transferred, nothing to stand behind.
Quentic: The name on the audit
In EHS, being wrong is expensive: fines, shutdowns, real safety exposure — so customers had little appetite to insource that risk. Being the system of record meant a customer could walk into an audit and pass it easily, the documentation and trail already in defensible form. An LLM won't stand in front of the regulator on their behalf.
Chegg: A library, not an asset
The answer library looked like accumulated data, but it wasn't proprietary or load-bearing. An LLM produces equivalent answers without it.
Quentic: Real friction, but exportable
Years of incident records, audit trails and compliance history raised the cost of leaving — but customers had the right to export all of their own data, which deliberately capped how much lock-in it created. Friction, not a wall.
Chegg: A channel that closed
The funnel came from students typing questions into Google and clicking through. When Google began answering those questions itself, the channel closed at the source.
Quentic: Strong at home, ceded elsewhere
Quentic held this layer, but only within its borders. In Central Europe the footprint was strong enough to be self-reinforcing. Elsewhere, there were whole industries we never entered, because an established competitor already owned the attention there — the experts, the relationships, the standing. In those verticals, deals closed before we even knew they existed. Not a technology gap we could engineer past; a distribution-and-authority gap, and close to unassailable.
The layers of the stack don't move. Regulation doesn't retreat, encoded knowledge doesn't decay, first-party data keeps compounding. What moves is everything outside them — how much AI can already do without you, and therefore how many of your customers still have to buy.
So picture your market as a pyramid. The most demanding customers sit at the narrow top; the least demanding at the wide base. Now draw a waterline across it. Below the line, the customer can have AI build it outright — or AI absorbs the job entirely. Above it, the complexity still justifies buying.
The line is not fixed. AI lifts it. And as it rises, your layers don't weaken — the set of customers they protect shrinks from the bottom.
Above the line: complexity still justifies buying.
Below the line: the customer builds it — or AI absorbs the job.
“The stack gives you altitude. The waterline gives you rate. You need both to answer the only question an owner actually has: how many years are left, and which layer goes first.”
Chegg's customers sat at the base of its own pyramid: students with routine questions, the widest and least demanding layer in that market. The waterline didn't cut through Chegg's category. It rose past the whole thing in one step.
Quentic's customers sat near the top: industrial operators tracking incidents and audits across multiple sites and jurisdictions, where being wrong means fines, shutdowns, or someone getting hurt. Well clear of the line. Same four layers, same rising water, opposite outcome.
“Which of your customers could do without you in eighteen months, and what share of revenue sits with them?”
Then ask it again about the customers you're still trying to win. That answer is the one that moves the multiple.