Methods of Adoption

Before I started actually working as a software engineer full time, writing code was this fun thing I was always trying to figure out on my own, and it was fun, and I could hardly sit down at my computer without learning something. These days, I do very little of this kind of work. I learn more about computers by doing my job and frankly, the kind of software I write for work is way more satisfying than any of the software I would end up writing for myself.

I think this is because the projects that a team of engineers can work on are necessarily larger and more impactful. When you build software with a team, most of the time the product either finds users (or your end up without a job.) When you build software with other people and for other people, the things that make software good (more rigorous design, good test discipline, scale,) are more likely to be prevalent. Those are the things that make writing software fun.

Wait, you ask “this is a lisp post?” and “where is the lisp content?” Wait for it…

In Pave the On/Off Ramps¹ I started exploring this idea that technical adoption is less a function of basic capabilities or numbers of features in general, but rather about the specific features that support and further adoption and create confidence in maintenance and interoperability. A huge part of the decision process is finding good answers to “can I use these tools as part of the larger system of tools that I’m using?” and “can I use this tool a bit without needing to commit to using it for everything?”

Technologies which are and demand ideological compliance are very difficult to move into with confidence. A lot of technologies and tools demand ideological compliance, and their adoption depends on once-in-a-generation sea changes or significant risks.² The alternate method, to integrate into people’s existing workflows and systems, and provide great tools that work for some usecases and to prove their capability is much more reliable: if somewhat less exciting.

The great thing about Common Lisp is that it always leans towards the pragmatic rather than the ideological. Common Lisp has a bunch of tools--both in the langauge and in the ecosystem--which are great to use but also not required. You don’t have to use CLOS (but it’s really cool), you don’t have to use ASDF, there isn’t one paradigm of developing or designing software that you have to be constrained to. Do what works.

I think there are a lot of questions that sort of follow on from this, particularly about lisp and the adoption of new technologies. So let’s go through the ones I can think of, FAQ style:

• What kind of applications would a “pave the exits” support?

  It almost doesn’t matter, but the answer is probably a fairly boring set of industrial applications: services that transform and analyze data, data migration tools, command-line (build, deployment) tools for developers and operators, platform orchestration tools, and the like. This is all boring (on the one hand,) but most software is boring, and it’s rarely the case that programming langauge actually matters much.

  In addition, CL has a pretty mature set of tools for integrating with C libaries and might be a decent alternative to other langauges with more complex distribution stories. You could see CL being a good langauge for writing extensions on top of existing tools (for both Java with ABCL and C/C++ with ECL and CLASP), depending.

• How does industrial adoption of Common Lisp benefit the Common Lisp community?

  First, more people writing common lisp for their jobs, which (assuming they have a good experience,) could proliferate into more projects. A larger community, maybe means a larger volume of participation in existing projects (and more projects in general.) Additionally, more industrial applications means more jobs for people who are interested in writing CL, and that seems pretty cool.

• How can CL compete with more established languages like Java, Go, and Rust?

  I’m not sure competition is really the right model for thinking about this: there’s so much software to write that “my langauge vs your langauge” is just a poor model for thinking about this: there’s enough work to be done that everyone can be successful.

  At the same time, I haven’t heard about people who are deeply excited about writing Java, and Go folks (which I count myself among) tend to be pretty pragmatic as well. I see lots of people who are excited about Rust, and it’s definitely a cool langauge though it shines best at lower level problems than CL and has a reasonable FFI so it might be the case that there’s some exciting room for using CL for higher level tasks on top of rust fundamentals.