"Curiosity doesn't kill the cat; it kills the competition." — Sam Walton

A partner came to me with a problem that was, technically, a billing problem. It was really a relationship problem.

There had been legitimate, defensible scope creep on a matter where the deal complexities had forced the work to expand. The client had not authorized the additional hours, and the partner needed to recover them by providing a narrative on the work and why it was essential.

Done manually, that would have meant combing through more than 4,000 rows of time entry narratives, separating useful evidence from noise. Hours of it, likely from one of the highest-billing timekeepers in the firm.

So I started with what I had: curiosity and a half-formed hypothesis. The tools were linguistically capable. If I pointed a model at time entries and their narratives, could it flag specific tasks? A few learning curves later: yes. Could it interpret the shorthand timekeepers use and connect it to broader assumptions about workflow? A few more iterations: also yes.

We ended up with a clean, accurate collection of entries organized by task and workstream. From there, we could synthesize the narrative and make the case. The client got clear, timely data organized in a way billing software, CRM, and Excel could not have produced on their own.

In law firms, time usually means money. This exercise was an initial time investment that would pay dividends later. That kind of investment is only made when someone has both the inclination and habitat to architect innovative solutions.

Also, I really did not want to read 4,000 rows manually.

That instinct, once fed, is hard to put back.

Curiosity is not hard to find in ambitious people. It is even easier to snuff out in environments that do not reward it.

This matters in legal pricing because the function is still young. The modern version of the role, with AFAs, matter economics, and AI-assisted forecasting, is not old enough for tenure to tell the whole story. The tools, the expectations, and the definition of “good pricing” are all moving at once. The goalposts are moving (occasionally, they appear to be sprinting).

In a mature, stable profession, tenure can be a reasonable proxy for capability. Legal pricing is not exactly a mature, stable profession. Firms practice it differently from each other. Each pricing conversation has its own mixture of math, judgment, psychology, and commercial strategy sitting underneath it.

In a field like this, imaginative innovation is a professional advantage that can determine whether a team merely survives or thrives.

The analysts who go looking without being told to look are how this function moves forward. A traditional years-of-experience filter may not capture that kind of skillset. Instead, it shows up in how someone talks about the work: what they notice, what they can see connections in, and what questions they ask when nobody is asking them to.

It is also easy to underestimate when it is sitting inside your own organization.

This is a signal firms should pay attention to. Underfed curiosity can look like restlessness, distraction, or impatience when it comes from someone internal. Then, when the same instinct shows up outside the organization as a product, platform, or new market entrant, we call it innovation (and usually end up buying it).

Max Junestrand built Legora without a legal background. Don Muir, who built F2 in answer to a frustratingly manual private markets workflow bottleneck, has publicly remarked curiosity can outrank intelligence in terms of value. Both of these founders made the existing way of working look slow by acting on the instinct to try something new.

Curiosity cannot be taught the way a pricing model or a reporting process can be taught. You can cultivate it, give it room, reward it when it shows up. You can also train it out of people.

The analyst who stops asking “why do we do it this way?” because the answer is always “because that is how we do it” is still competent and reliable. They are still value-adds.

But something has been lost.

Missing the unusual candidate is one version of the risk. The other is slower: over time, you can teach curious people to stop being curious. You can take the people most likely to improve the system and train them to survive it instead.

As for everyone who was told, at some point, that their curiosity was too much: I have a feeling they’ll be the ones selling you their ideas soon enough.