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Nice, sounds like it saved you some time.
You "AI" enthusiasts always try to find a positive spin :) What if I had trusted the code? It was working after all. I'm guessing that if i asked for string manipulation code it would have done something worth posting on accidentally quadratic.
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Just for the record, Photoshop's first generative 'AI' feature, Content Aware Fill, is 15 years old. That's a long time for Adobe not to have figured out what your are saying.
Photoshop is unapproachable to the 99%. A faster GPT 4o will kill Photoshop for good.
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This typically happens when you run the chat too long. When it gives you a new codebase, fire up a new chat so the old stuff doesn't poison the context window.
Why isn’t it smart enough to recognize new contexts that aren’t related to old ones?
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Photoshop is unapproachable to the 99%. A faster GPT 4o will kill Photoshop for good.
Not a chance. Photoshop is about having maximum control and power. AI requires relinquishing a degree of control in exchange for speed. Totally different audiences.
The premise might possibly be true, but as an actually seasoned Python developer, I've taken a look at one file: https://github.com/dx-tooling/platform-problem-monitoring-co... All of it smells of a (lousy) junior software engineer: from configuring root logger at the top, module level (which relies on module import caching not to be reapplied), over not using a stdlib config file parser and building one themselves,…
How do you properly configure a logger in application like that?
There are plenty of ways to structure code so this does not happen, but simply "do not do anything at the top module level" will ensure you don't hit these issues.
I completely agree, as a fellow senior coder. It allows me to move significantly faster through my tasks and makes me much more productive. It also makes coding a lot less painful because I'm not making typos or weird errors (since so much code autocompletes) that I spend less time debugging too.
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The more I browse through this, the more I agree. I feel like one could delete almost all comments from that project without losing any information – which means, at least the variable naming is (probably?) sensible. Then again, I don't know the application domain. Also… def _save_current_date_time(current_date_time_file: str, current_date_time: str) -> None: with Path(current_date_time_file).open("w") as f: f.write(…
>The scary thing is: I have seen professional human developers write worse code. This is kind of the rub of it all. If the code works, passes all relevant tests, is reasonably maintainable, and can be fitted into the system correctly with a well defined interface, does it really matter? I mean at that point its kind of like looking at the output of a bytecode compiler and being like "wow what a mess". And it's not li…
People have different definitions of "reasonably maintainable", but if code has extra stuff that provides no value, it always perplexes the reader (what is the point of this? what am I missing?), and increases cognitive load significantly.
But if AI coding tools were advertised as "get 10x the output of your least capable teammate", would they really go anywhere?
I love doing code reviews as an opportunity to teach people. Doing this one would suck.
I start every piece of work, green or brown, with a markdown file that often contains my plan, task breakdown, data models (including key fields), API / function details, and sample responses.
For the tool part, though, I took a slightly different approach. I decided to use Rust primarily for all my projects, as the compile-time checks are a great way to ensure the correctness of the generated code. I have noticed many more errors are detected in AI-generated Rust code than in any other language. I am happy about it because these are errors that I would have missed in other languages.
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Why do you HAVE TO one-shot? No one says you have to code like those influencers. You are a software engineer, use AI like one, iteratively.
>No one says you have to code like those influencers. You are a software engineer, use AI like one, iteratively. This is my issue with all the AI naysayers at this point. It seems to all boil down to "haha, stupid noob can't code so he uses AI" in their minds. It's like they are incapable of understanding that there could simultaneously be a bunch of junior devs pushing greenfield YouTube demos of vibe coding, while…
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Nah. This isn’t true. Every time you hit enter you’re not just getting a jr dev, you’re getting a randomly selected jr dev. So, how did I end up with a logging.py, config.py, config in __init__.py and main.py? Well I prompted for it to fix the logging setup to use a specific format. I use cursor, it can spit out code at an amazing rate and reduced the amount of docs I need to read to get something done. But after its…
Are you reading a whole encyclopedia each time you assigned to a task? The one thing about learning is that it compounds. You get faster the longer you use a specific technology. So unless you use a different platform for each task, I don't think you have to read that much documentation (understanding them is another matter).
In some ways this is even more impressive -- every prompt you make, your LLM is in effect re-reading (and re-comprehending) your whole codebase, from scratch!