Thanks to all posts above for engaging with my quest for minitab style text character dotplots!
Below is an example of what I'm on about (artisan construction in Mousepad) and apologies to anyone on a narrow screen where the text mode is going to get jumbled.
Hmm, here's a thought... If you want to stand out, it doesn't matter that some things now are easier for everybody, what matters is that that you are able to get better results than others. Learning multiple languages gives you more the ability to use them. It improves your thinking, makes you a better coder, and more able to understand different techniques. LLMs are tools, to use them better than the next person you need to understand what to ask, and what a good answer looks like.
Exactly. If nothing else, writing a solver in Python or Java might take dozens or hundreds of lines more code than Prolog, so simply knowing what tools are best for what jobs helps you be a better developer, whether you're using a compiler or an agent.
Sure, but that's about thinking and describing in more high-level English, not individual programming languages. That era is over.
Advice to juniors (say) to spend time learning multiple programming languages over good command of a single one, deep expertise in LLM use and basic software engineering principles is going to severely undermine their value in an already tough field for entrants. For seniors there will generally already be a reasonable grounding in multiple paradigms; delving much further into legacy manual coding styles is going to see them leapfrogged by experts in modern (ie AI-assisted) approaches.
It is restricted in a way that you would restrict yourself to write high speed software in most languages, and I found it is not that restrictive compared to C that you would have to use if you were to write a fast Python library.
oh for sure, but I still feel like telling people pypy is written in python is misleading. it's written in something significantly like python, but it's not python.
The fact that it's written in python is often brought up in order to explain its name. But really, it's much less interesting than the fact that it has a tracing JIT. If it were called PyJIT I'd bet it would be clearer and more obvious that it's fast. And people would prob get less hung up on the distinction between python/rpython.
If those numbers are true, they could tart with one Mac and can double every few months. But, I guess there are also many people who do not have ready access to whatever a Mac mini costs either...
No , boring notch is a Dynamic Island like utility and it also hasn’t been updated since November , I suggest you to try out atoll which is a fork of it and pretty great .
I don't necessarily agree with that... I think that it's a matter of perspective. I find that AI tends to make a lot of the same errors I've seen from actual developers, especially when interacting or leading foreign dev teams.
When I spend a lot of time in planning mode, I tend to get a lot more value out of the output and have to redirect far less. It also helps to establish your API interfaces, reference points, interactions, behaviors and even a lot of the test harnesses ahead of development cycles. You need to define a lot more ahead of letting it go.
I would say that I'm getting maybe 2.5x the value and 5-10x the output from AI... by value, I mean what the end user/customer cares about... by 5-10x I'm including the increased documentation, testing, etc.
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