One problem with this that many orgs face is that later down the road when your business has grown, now you need to hire a lot of specialists (usually in a big hurry), and in fact at that point hiring the new specialists often matters way, way more than continuing to take care of the generalists who got you to that point.

On one hand, if you defer to the market, you'll end up being forced to pay high wages to those later-on specialists, and probably also more equity than would otherwise be warranted for their time of entry to the firm. Lots of early-on generalists could get mad that they aren't paid well and that even if they have more equity, it's not fairly proportioned to how much up-front work they put in.

On the other hand, if you don't agree with this market problem, then you end up hiring only specialists who don't know how much they are worth, or else have other factors that make them cheaper to hire -- generally meaning you hire crappier later-on specialists to save money and to keep the equity proportions "fairer" to the early-on generalists. These firms often get a bad reputation for doing crappy work in the specialist area, and specialists stay away from it.

I see this a lot with machine learning. A smart machine learning specialist is not going to join a Bay Area start-up for $150k and 0.1% equity as employee number 40. If you waited until employee 40 to start investing in highly specialized machine learning talent, and it's something your business needs, then you're either going to have to raise the wage super high (much higher than the early-on employees who may resent this), or you're going to have to offer completely disproportional equity, or both; or else, you're going to have to hire inexperienced and/or crappy people who don't mind taking a job as employee #40 for that kind of "conventional start-up wisdom" pay/equity range.

To me, this suggests one hypothesis is that start-ups preferring generalists is actually a bad idea. Instead, they should excel at forecasting which specialists they'll need, then hire the best of that speciality very early on. To entice them to put up with generalist work for a while, pay them a lot or give them better than market equity, and be as flexible as possible with what kinds of working style / environment you offer them.

Then when the time comes to really turn up the heat on specialist labor, you'll already have the specialists, and they'll already know how the systems work. At that point, you can expand hiring on the generalist front, which should be relatively easier to do at the current start-up wage level, and have those later-on generalists take over the maintenance and generalist work from the early-on specialists.

This is way easier said than done, of course, but it would be interesting to see whether there's a relationship between start-ups that succeed and start-ups that choose to specialize early and generalize later. Most start-ups fail, and anecdotally, most start-ups also seem very inflexible about accommodating what an early-on specialist might want (like say, to avoid working in Agile or to work in a quiet office) and seem more geared toward hire pools of generalists (mandate team-wide Agile, have lots of social outings, use open-plan offices). Maybe this is a big part of going wrong?