![]() ![]() ![]() AI tools are trained on code from thousands of real projects with disparate levels of quality and completeness-that is, code that almost always runs and usually gets the job done, but is only occasionally reliable, maintainable, secure, or bug-free. The reason for this rosy first impression is that the problems are hidden under the surface. And when you paste it into an IDE and it actually works, it feels like you’ve cracked the industry wide open. From there, you can ask for tweaks and bugfixes until you’re satisfied with the output. It’s a seductive experience: you can ask it to write an application in any major programming language and it will spit out code right up to the token limit-more than enough space for the typical “tutorial-sized” app. Many people’s first taste of programming came this year in the form of a ChatGPT conversation. Let’s take a look at what AI means for developers (and non-developers) at every stage. What matters isn’t just whether you use it, but how. AI could be the tool that fast-tracks your career or it could be the obstacle that derails it. But despite having arrived for junior, mid-level, and senior engineers all at once, not to mention people who don’t know a struct from a hole in the wall, the risk/benefit calculation couldn’t be more different depending on your level of experience. AI-powered programming tools have made a splash in the programming world, and they’re probably not leaving anytime soon. And if generative AI’s greatest strength is its ability to model and imitate patterns, forming a fluid interface between humans and machines- as I’ve previously argued-wouldn’t programming be the ideal use case for it? If anyone could write good code, it would be a computer. ![]() It’s predictable to a fault, which is why computers (and some humans, like myself) are so compatible with it. Patterns and repetition are its bread and butter. It has a small, unambiguous vocabulary and unbreakable syntax rules. Still, there’s a compelling case for AI as a programming tool. I’m trying my best not to gloat about it. The promised wave of apps built entirely by AI never materialized. Now anyone with an Internet connection could ask an AI model to write the next big social media app, in JavaScript please, and throw in some blockchain while you’re at it. Early in 2023, this discovery caused a lot of premature celebration among LinkedIn influencers: no longer was there any need for seasoned developers with their gatekept expertise, fastidious attitudes, and inconveniently high salaries. Large language models (LLM) like ChatGPT write very convincing code snippets. ![]()
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