81–90 of 388 posts
So how many developers in that survey are those? They surveyed 791 developers (:D) and "a third of senior developers" do that. That's... generiously, what... 20 people? It's amazing how everyone can massage numbers when they're trying to sell something.
Seems about right for me (older developer at a big tech company). But we need to define what it means that the code is AI-generated. In my case, I typically know how I want the code to look like, and I'm writing a prompt to tell the agent to do it. The AI doesn't solve any problem, it just does the typing and helps with syntax. I'm not even sure I'm ultimately more productive.
This article goes completely against my experience so far. I teach at an internship program and the main problem with interns since 2023 has been their over reliance on AI tools. I feel like I have to teach them to stop using AI for everything and think through the problem so that they don't get stuck. Meanwhile many of the seniors around me are stuck in their ways, refusing to adopt interactive debuggers to replace…
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Neither are you if that's your understanding of a senior engineer
I think the parent commentors point was that it is nearly trivial to generate variations on unit tests in most (if not all) unit test frameworks. For example: Java: https://docs.parasoft.com/display/JTEST20232/Creating+a+Para... C# (nunit, but xunit has this too): https://docs.nunit.org/articles/nunit/technical-notes/usage/... Python: https://docs.pytest.org/en/stable/example/parametrize.html cpp: https://google.gith…
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I think the parent commentors point was that it is nearly trivial to generate variations on unit tests in most (if not all) unit test frameworks. For example: Java: https://docs.parasoft.com/display/JTEST20232/Creating+a+Para... C# (nunit, but xunit has this too): https://docs.nunit.org/articles/nunit/technical-notes/usage/... Python: https://docs.pytest.org/en/stable/example/parametrize.html cpp: https://google.gith…
Parameterized tests are good, but I think he might be talking about exercising all the corner cases in the logic of your function, which to my knowledge almost no languages can auto-generate for but LLMs can sorta-ish figure it out.
I wouldn't say I'm old, but I suddenly fell into the coding agent rabbit hole when I had to write some Python automations against Google APIs. Found myself having 3-4 different sites open for documentation, context switching between 3 different libraries. It was a lot to take in. So I said, why not give AI a whirl. It helped me a lot! And since then I have published at least 6 different projects with the help of AI.…
I love the split personality vibe here.
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I think the parent commentors point was that it is nearly trivial to generate variations on unit tests in most (if not all) unit test frameworks. For example: Java: https://docs.parasoft.com/display/JTEST20232/Creating+a+Para... C# (nunit, but xunit has this too): https://docs.nunit.org/articles/nunit/technical-notes/usage/... Python: https://docs.pytest.org/en/stable/example/parametrize.html cpp: https://google.gith…
The useful part is generating the mocks. The various auto mocking frameworks are so hit or miss I end up having to manually make mocks which is time consuming and boring. LLMs help out dramatically and save literally hours of boring error prone work.
I'm not a coder but a sysadmin. 35 years or so. I'm conversant with Perl, Python, (nods to C), BASIC, shell, Powershell, AutoIT (int al)
I muck about with CAD - OpenSCAD, FreeCAD, and 3D printing.
I'm not a senior developer - I pay them.
LLMs are handy in the same way I still have my slide rules and calculators (OK kids I use a calc app) but I do still have my slide rules.
ChatGPT does quite well with the basics for a simple OpenSCAD effort but invents functions within libraries. That is to be expected - its a next token decider function and not a real AI.
I find it handy for basics, very basic.