A lot has been written about “hyperproductive teams”, and a lot has been written how programming languages help here. Beating the Averages is probably the most famous one. I myself worked in Smalltalk full-time, and can share the same kind of story. So why aren’t we all using either of these two languages?

When I created my own startup, an Internet hosting company, I went down the same path as Paul Graham: two coders, me and a full time one, a VisualWorks Smalltalk license, and we managed to develop something that was utterly impressive given that we had 1.5FTE on the job. Hosting provisioning, accounting, all sorts of really advanced stuff around whole-sale packaging, multiple currencies, and so on. Later on, I worked at a larger Smalltalk shop and between 5-6 developers we completely beat large companies employing ten times as many people. So why aren’t we all using either of these two languages?

I can recite many of such stories; of people keeping up with their ten person team by coding whatever the team did during the day in 2-3 hours at night using Squeak Smalltalk; about an old Lisp hacker working in a research setup with mostly Java colleagues and always estimating to need 10% of the time (and then actually making the estimate). So why aren’t we all using either of these two languages?

The answer is multifaceted, of course. There’s a fear, often more with management than actual techies, of choosing a non mainstream language because hiring for that language will be too hard (wrong). Tooling for niche languages often is not as good as for mainstream stuff (quick, find a way to deploy a Pharo Smalltalk image on EC2 or in a container). The list goes on and on and usually every point can receive the same reaction: yes, that might be true, but if the payoff is that big, why not make the investment?

However, there’s one thing in common between all the stories I’ve heard and the successes experienced first hand: small teams. Every single time, you are looking at a software development shop with a grand total of, say, less than a dozen developers in a pretty stable setup.

And that, I think, is the only way to use these very powerful languages (and do not forget: they are that powerful). Because, each in its own way, these languages encourage you to solve your problem in two steps:

Create a language to solve your problem; Solve your problem.

Lisp is more explicit about this, but I opened an old Smalltalk image and the “application” language ended up being very high level, very domain specific, and just as hard to grok as your average macro-ridden Lisp system.

These languages are very powerful, but they don’t scale. So even when you get ten times the productivity, the mostly tribal complexity will not scale beyond your “pizza-sized team” and therefore you now have a hard upper limit on your total software development capacity.

Harsh, isn’t it? But I cannot find counterexamples. Whereas I can find plenty of examples of teams using “normal” programming languages (Java, PHP, Python, Ruby, or newer entrants like Elixir or even Golang) that breeze through the 100, 200, 500 developer marks without much trouble. So I must conclude that there seems to be a scaling limit.

Why? My theory, completely made up and untested, is that these powerful Lisp/Smalltalk systems weave code and brains together in a way that amplifies both. It’s very organic, very hard to document, and thus it becomes very hard to absorb new brains into the system. When I joined the small Smalltalk group it was very hard to get started in that codebase. It was complex, and completely different from the previous thing I worked on. Both were using the same VM (VisualWorks) but both had their IDEs adapted to a point that they became new and very well-honed tools and new things in their own right. In Smalltalk, there’s no difference between writing “business” code and writing “tooling” code, and even no difference between that and changing your IDE, so everything happens interchangeably and fluidly and you end up with an IDE that’s adapted for the problem at hand, not for everybody’s generic problems. It’s hard to ramp-up in these environments and certainly in the light of the short retention times these days, likely won’t work.

And on that terrible disappointment… I think I’ll end while hoping that someone out there on planet Earth reads this and proves me wrong :)