22Oct

Generalists Beat Specialists Most of the Time, But Try Telling Hiring Managers That

Posted by Elf Sternberg as Uncategorized

I’m 53 years old and still consider myself a software engineer who’s professional job isn’t writing code, it’s producing value using coding skills. I took a year off to learn recently to go back to school, and trying to find a job when I’m 53 turned out to be a challenge. I do think I encountered a lot of ageism in the interview process, but I also think that taking a year off left me vulnerable to skill rot.

Fortunately, I did find a job, and my current employer looked past the rustiness to see that I could do the job he needed me to do. And this week I had an experience that, well, frankly, has me going, "To hell with the ones who didn’t hire me."

In my last job at Splunk, I wrote a lot of Go, a lot of OpenAPI, a little bit of Docker, a little bit of Kubernetes, a little bit of AWS, and a modest amount of React. In previous jobs, I had written tens of thousands of lines of Python, Javascript, CSS, and HTML, as well as shell scripts, Perl, C/C++, even some Java, along with all the maintenance headaches of SSH and so forth.

In my year off I spent my time taking classes in low-level systems programming: Programming Languages and Compilers, and I have a half-finished implementation of a PEG parser based on an obscure algorithm for parsing and lexing that nobody has ever fully implemented in a systems language. I chose Rust as my language of choice because its performance is close to C++’s and its compiler choices are sensible and helpful.

In my new job, part of my task involves helping the team "level up." They’re mostly SDET-1s (Software Development Engineering in Test, level 1) producing tooling for the Quality Assurance teams, who spend a lot of their time playing games (it is a gaming company) and then reporting on any problems they found. The QA folks aren’t the sort to be working in JIRA or Bugzilla, they needed a straightforward tool that understands their needs.

The tool they’ve built is in Django, which is great for prototyping, but it’s now hitting its limits. Meanwhile, we’re all "moving to the cloud," as companies seem to like to say these days, and my current big side project is to write a demo on what a cloud-based solution looks like. I decided to take two pages from the existing app (the login page, and the list of existing reports) and make them work.

I spent two to four hours a day over eight days, and in those eight days here’s what I have learned (and hopefully will document soon):

  • React Hooks
  • React Context
  • Material UI
  • Material themes
  • Golang’s LDAP interface
  • Golang’s Postgres interface
  • CORS
  • JWT & PASEO
  • Multi-stage Docker builds
  • Docker swarm
  • Docker stack

I knew a little bit about each of these. I did the demo yesterday, using live data, and jaws dropped. "That was fast" (It’s not Django) and "Have you seen our tooling? That looks better than anything else! It looks like us." (I found the company style guide and applied the colors and fonts to the Material Theme engine). Then the reveal: The Django app container is 2.85GB, but my project fit into 37MB; an automated security scanner screams in horror when examining the existing project, but mine had only one error: it’s a demo, so I didn’t have a "good" SSL certificate.

Some of these things (like multi-stage builds) I’d only ever heard about. But the simple fact is that none of this is particularly new. Hooks just wrap ordinary React; React.Context is just React.State writ large. Material is a just a facade, themes are just well-organized CSS styles, Golang’s interfaces are a lot like Python’s or Rust’s, LDAP is just a query engine with an annoying call sequence, JWT is just Web Cookies with some rules. Swarm and Stack are variations on Kubernetes and Compose. Multi-Stage builds were… Makefiles, "but, like, for the cloud, dude."

In almost every case I already had a working mental model for each feature, I just needed to test and see if my model was accurate and adjust accordingly. Some things are still fuzzy– docker networking is fun and seemingly sensible, but I haven’t memorized the rules yet.

I can contrast this with my academic pursuits, like Rigged Regexes and Seam Carving, which are both taking forever. Part of the reason they’re taking forever is that they involve genuinely new ground: no one has produced a systems-language implementation of Brzozowski’s Algorithm, and I have yet to find a multi-threaded, caching implementation of the Seam Carving algorithm for a low-level Unix environment like ImageMagick or NetPBM. (Another part now is that, hey, I’m working full time; I get like 30 minutes every day to work on my Github projects, usually during the commute.)

In short, the people who didn’t hire me didn’t hire me because, if I were a construction worker, they were an all-Makita worksite and I owned a DeWalt drill.

Which is absolutely nuts. But that’s the way this industry works.

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