All public forums have an astroturfing problem including this one
Google, Apple, Microsoft, Amazon, Facebook, etc they all have hundreds of thousands employees and even if they are not explicitly paid to astroturf, they try to be subconsciously loyal to their employer, downvoting everything that goes against their subtle wiring, and happily upvoting every new product or feature launched by their org
Just checking help/about Scissors shows how detail oriented you are. As the saying goes, you paint the wall at the back of the dishwasher so the plumber knows you have good taste
I was going to ask the same, perhaps do it myself as a side project. I see value in it, it definitely should be an app. Swift for MacOS, Rust for Linux (no tauri, react, nothing, just plain optimized rust)
DeepSeek can do it in the blink of an eye, here is what I would do:
- Copy the source to scissor-web, create an empty sibling folder scissor-macos and another as scissor-linux
- Run DeepSeek Harness, create a workspace pointing to scissor-macos start a session and tell DeepSeek to port your excellent app located in folder scissor-web using the latest swift for macos 26
- Watch magic performed for your own delight
- Once finished, do the same for scissor-linux
A couple of hours later you will have three beautiful apps for web, macos and linux. Then ask DeepSeek to translate them to chinese, french, german, italian, spanish, portuguese, russian, etc
Then you will see software development with different eyes
As a programmer, today I can confirm with no room for doubt that programming is dead (programming by humans to be precise, the act of typing code on a premise to present a solution to a problem)
We may consider ourselves the last programmers before the AI era
This is the perspective, not code, coding is solved. The wrong input will produce wrong outputs, so a mediocre dev using AI may produce mediocre results. AI can do everything asked for, code, tests, reviews, fixes, etc but still it can not think, for now
Intelligence is the new currency, but it will be short lived
> forcing companies to increase the quality of their developers
Just don't. Fire them! AI is better than a thousand devs. What you need is testers that know what to test that AI can't, not code or UX/UI (not talking about playwright here) but business intelligence if that is testable, the things that produce results (profits) and the reason it was asked for in the first place, to solve a problem
If the problem was asked wrongly, the result will be wrong too. Fire devs, then PMs, then IT Managers if they really don't know how to outperform AI, and that's exactly the point, they won't be able to do it in code or tests or reviews, only in intelligence, for now...
Code is solved, no discussion about that. Whatever piece of code you think you can do better than AI, you my friend, are wrong. There will be people that will take months, perhaps years to understand that but make no mistake, code is solved and apps will cost nothing to build, nothing to copy and nothing to implement or maintain
And the good thing? it will get better, faster and cheaper than free. You can't see it? Not my problem, all yours, get your harness du jour and start learning, well no, you will be laid off no matter what you do, so, I have no advice to give
> code is solved and apps will cost nothing to build,
it probably depends on apps. For some generic boilerplate fitness tracker maybe.
But I write some complicated code daily using all Frontier models (I switch between them), and in all cases it takes many back and force iterations to get to the code quality (clean design, no obvious bugs) up to my standards.
There is absolutely not a single line of code human created, no matter how abstract or esotheric, that an AI model can not code faster, cheaper and better. None, not one, in the whole history of mankind and computing
Now, code generated by AI, of course it takes time to generate by our current models, trillions of parameters analyzed to produce an output takes time and resources. You don't take credit for that, I stopped doing that. It is the model that deserves the credit. We are not writing complicated code, we are delegating that to AI models and they make take time to resolve the problems they may face, but they still will do it a million times faster than the best of us
You aren't coding though. The LLM is coding and you are specifying.
It is just a function. A next token prediction function. Garbage-in/Garbage-out is as true as ever.
Coding is solved. Specification and translating requirements into specifications is an unbounded domain and unsolvable by definition.
What LLMs change is that now you develop the specification through iterative implementation and testing.
You start with a weak specification which produces slop, then you progressively build the specification with different approaches to automated testing. The tests are the specification. Ultimately, what you ship is the tests. They are the only thing that proves the functionality of the program. An LLM can produce code that passes any test suite you give it. If the result is bad, the problem is not the code, the problem is the specification.
Google, Apple, Microsoft, Amazon, Facebook, etc they all have hundreds of thousands employees and even if they are not explicitly paid to astroturf, they try to be subconsciously loyal to their employer, downvoting everything that goes against their subtle wiring, and happily upvoting every new product or feature launched by their org
That's just human nature, proven in 3, 2, 1...
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