![]() ![]() Sure there is a lot of creativity in engineering, but there is usually a whole area of math known to be suitable for expressing solutions clearly, given the area of engineering.Ĭontrast with the utter lack of standard notation across software tools and implementations, for describing all the trade offs, gotchas, glue, historical drift & complexity, theories of memory, caching, user affordances, potential overflows, races, etc. Well, most engineering fields have well defined applied math that spans from the problem domain to the solution domain.Īlgebra and calculus for analog circuits, most physical objects, properties and processes.ĭifferential equations for dynamical systems and dynamical behaviors. It just isn’t as publicly documented as it is software, probably because it’s hard to build an open source bridge. You don’t get a good result without a healthy dollop of wisdom, experience, educated guesses, and a handful of fuckups (which hopefully you notice before you let people use the thing).Įngineering in other disciplines is no less messy, haphazard, and experimental than it is in software. Doesn’t matter if you’re building a web browser, a motherboard, or a bridge. Really the core of engineering is just a very broad set of practices and principles that allows people to solve poorly characterised problems using maths, physics, enormous amounts of experience, intuition, heuristics, wisdom, patterns, educated guess etc in a reasonably consistent and repeatable manner. Engineering in other fields is just as much dealing with poorly characterised problems as it is when writing code (it takes quite a lot of characterisation to go from “we want a bridge here”, to an actual damn bridge, and that’s all an engineers work). ![]() > Engineering - solving well characterized problems based on math and physics (which can include materials with known properties, chemistry, approximations, models, …), and well defined areas of composability (circuits, chemical processes, structural design, …)Įh, I think you’re overselling how precise and well defined engineering is in other fields. So in a way it feels like LLMs are going to make you a "worse" programmer by doing the work for you.ĭoes anyone feel that way? Maybe I am wrong and the technology hasn't really clicked for me yet. To become proficient I need to write a lot of code, but the more I use LLMs, the less repetitions I get in. ![]() I am only able to check the correctness of the code, if am am proficient enough as a programmer (and possibly in the language as well). It is also more exhausting than just writing the thing myself.Ģ. At least for me, having to be creating prompts and then reviewing the code that generates is slower and takes me out of the flow. When I wrote the code, I know it by heart and I know what it does (or is supposed to do). It is my belief that if you are proficient enough in the task at hand, it is actually a distraction to be checking "someone else code" over just writing it yourself. I am also hesitant about the statement that it makes us 5 times as productive because we only need to "check the code is good" for two main reasons:ġ. So in a way it feels like a better "Google" but still I would rank it as inferior than Stack Overflow. So far my experience is that ChatGPT is great for generating code from languages I not proficient in or when I don't remember how to do something and I need a quick fix. Sure, the ability of LLMs to generate "decent" code from a prompt is pretty impressive, but I don't think they are biger than Stack Overflow or IDEs. ![]() I personally feel the technology is over-hyped. And on the coding front, they’re the biggest thing since IDEs and Stack Overflow, and may well eclipse them both. LLMs aren’t just the biggest change since social, mobile, or cloud–they’re the biggest thing since the World Wide Web. ![]()
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