Technology Evangelist

AI coding assistants have become basically omnipresent at this point and it’s honestly just crazy to think how quickly it all happened. I remember when Copilot first came out and was met with this weird mix of “is this magic” and “ugh this is so buggy”. And now there’s Claude doing full re-factors, ChatGPT giving you a complete project from a couple sentences description, and a dozen other smaller tools which honestly sometimes do a better job at small things than the big generative models. But here’s the thing, the tools… well… aren’t going to be replacing developers any time soon (I’m dropping the hot take now) but they are DEFINITELY shifting the types of work that we do.

I won’t beat around the bush on this one, it takes a particular kind of person to excel at this. Developer evangelism is objectively a ridiculous job in terms of skillset requirements. Coding-wise, you’ve got to be good enough that developers are not immediately dismissive when you share code with them, but not so good that you end up in engineering and never speak to another human. (I like to think I’m good at both though, what can I say? Dual threat.) Speaking is an obvious prerequisite. Presenting, after all, is a key part of the job. Workshops, podcasts, tweets half the time, when a JavaScript framework you use every day drops a breaking release at 2am. Writing, too, is key, because much of evangelism is written, in blog posts, documentation, GitHub READMEs that are…readable? Wow that’s rare when I think about it. Oh, and you better have the gift of the gab on top of all of that, or your community just won’t vibe with you. It’s a difficult thing to explain. Some days when I see the line-up for the next tech conference, I just shake my head at what people have to put up with to be great at this job.

The downside is… the code produced can be meh? Like it works but isn’t good. It’ll do what you asked but often with missing edge cases or will produce something correct but an older dev will cry during code review (I myself have committed at least one of these heinous things that’s technically correct but no one should write). I’ve seen AI functions with massive responsibilities or doing too many things all in one go, or writing a correct answer but in an unnecessarily slow manner. It’s using pattern-matching to generate answers but it does not actually understand performance so it can do really stupid things. So of course you need to review everything super duper carefully (learned that the hard way after shipping a bug that was literally right there in the suggested code by AI)

Truth is, this is what an actual day (for the most part, but I’ve spoken to dozens and they’re all similar) looks like: Mornings tend to be writing of some sort—docs, blogs, sample code, Twitter threads. Afternoons are sometimes internal meetings where you’re either arguing with product teams to get a bug fixed that will be embarrassing if you can’t demonstrate the feature at that conference event next week, or convincing product teams that yes, this feature that everyone’s asking for is important. (Internal arguments are very, very common for this job, FYI.) Evenings is when you “engage the community,” because developers are night owls, and they will be most active on Discord or Slack or whatever platform your community is hanging out on, then it’s evenings. Weekends? Blurred into work all the time, because there’s a hackathon or conference or something. This is why the burnout rate is through the roof.

Security is also… yeah we gotta talk about the security landmines. AI models will write perfectly working code with hardcoded passwords or SQL injection flaws if you’re not super careful. They don’t “natively” have a sense of security best practices, they just pattern-match them from what’s in their training data. And a lot of that training data is random GitHub repos with shitty insecure code, so it’ll be what it is. You HAVE to be diligent about reviewing everything with a security mindset, AI will not do that on its own.

Junior devs are getting maybe too reliant on these tools, I think. I think if you never learned how to actually read documentation or grok the fundamentals because you just ask AI for all the answers… that’s going to come back to bite you later. These tools are supposed to augment your skillset, not replace learning the basics. I mean, senior devs use the tools heavily too so this isn’t meant as an attack on juniors, but seniors can usually tell when the AI is spewing garbage or taking an objectively bad approach because they have the years of experience to recognize. Juniors will often blindly accept… or not recognize they’re being blindsided. Which is not good.

Code reviews and team dynamics are also changing in some very subtle but real ways as well and I don’t think this has really been talked about enough. For one, code reviews are now ALSO checking what a human accepted from an AI, which means you’re not just reviewing your teammates code but the AI’s as well? The bar feels different? You start to get this “oh the AI also suggested it” fallacy creep in as well. Onboarding people is weird now because you have to teach them not just development but how to properly use these AI tools, which is kind of… a skillset in its own right?

Productivity is increased though and I don’t think anyone can deny that. I am getting features released probably 40% faster than I was two years ago, in part thanks to these AI assistants. Tasks like writing tests (I hate writing tests more than almost anything) or documentation or database migrations or whatever are necessary but highly tedious. AI doesn’t get bored or tired so it’ll happily churn out 50 unit tests while you work on the actually interesting parts. That’s valuable.

Man, I don’t even know what to say about the future of this work, other than I think AI is going to upend the whole thing. If a developer needs sample code, it’s now a five-second Google search or chat with ChatGPT. “I’m having this error” doesn’t need to mean “please join our Discord server.” So does this make evangelism less relevant, or more? Does the human connection mean more because the bread and butter tasks have been automated? Likely a little of both. The work is morphing and evolving already, whatever happens with tech. Five years ago, developer livestreams were not a thing. Ten years ago, Twitter was not the primary form of communication between dev and evangelist. No one knows what the hell’s next.