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The main thing I see (and it is possible I’m biased by some of these same factors), is that it does seem to make some moderately helpful tools? Like coding assi

The main thing I see (and it is possible I’m biased by some of these same factors), is that it does seem to make some moderately helpful tools? Like coding assistants, to knock out boilerplate. Maybe if it could make a developer twice as effective, it could halve the developers to project ratio. Jevons paradox, and we get twice as many projects, great. But the management requirements would be different, right? If teams are half as large, wouldn’t expect management to just, like, go away. But the tree might be able to lose some middle “summarize and pass up” levels, right?

deleted 2y ago
[deleted]
orwin 2y ago
Basically it helps with really generic stuff, but writing generic stuff isn't my job. I have access to windows copilot pro (basically ChatGPT 4 Turbo/ 4o depending of the time of the day) as a tester, and github copilot as a user, i can say without hesitation that ChatGPT is sightly better to write comments, but both are bad to do anything harder than writing HTML forms, at least from scratch. They _are_ a great rubber duck though, today i had a concurrency issue and asked windows copilot for solutions. It was wrong, but gave me an idea, basically saving me at least 45 minutes. Github copilot is a great autocomplete, saving me some time too, but i don't think it can make me twice as effective as a coder. 20%? Maybe 40% if i take into account the fact that it generate really good test cases (that i still have to read)? But coding is like 25 percent of my job, database/object design and software architecture are like 30%, network security another 25%, and the rest is meetings/coordination, so all in all, i don't think you can halve teams because you give them good genAI