1,583 karma · joined April 10, 2012
One small annoyance with your app is the instructions in the welcome were tiny. Took me well over a minute to figure out how to control the thing, until I finally found those small hand icons in the right corner. You should consider adding these to the first page of welcome using a large-er size or something.
- Use a word like "science" to lure in the geeks
- (you don't even need to know what science is, its ok)
- Some of the geeks will push your headline to top of HN just because it had the right word in it
- Put some filler about life being hard in the article, so those who actually read it have to waste ten minutes of their lives (proving your point).
- Profit and glory!
This tool on the other hand is all about "jam as much work as you can come up with into being created in parallel". Obviously there is no managing of any flow of quality outputs, and no limiting of any work because you just shove everything into the agent and burn tokens like crazy.
Calling this a "Kanban" really irks me ... its like blasphemy or something.
Human cognition improves the more you practice it. Not when you outsource it to machines that do the "cognition" for you.
Clicked the link expecting to see some tool or method that actually allows graph-like queries and traversals on files in a file system, all I found was some rant about someone on the internet being wrong.
Waste of time.
Regarding training, we have many binaries all around us, for many of them we also have the source code in whichever language. As a first step we can use the original source code and ask a third party model to explain what it does in English. Then use this English to train the binary programmer model. Eventually the binary programmer model can understand binaries directly and translate them to English for its own use, so with time, we might not even need binaries that have source code, we could narrate binaries directly.
Who said that creating bits efficiently from English to be computed by CPUs or GPUs must be done with transformer architecture? Maybe it can be, maybe there are other ways of doing it that are better. The AI model architecture is not the focus of the discussion. It is the possibilities of how it can look like if we ask for some computation, and that computation appears without all the middle-men layers we have right now, English->Model->Computation, not English->Model->DSL->Compiler->Linker->Computation.
The difference is, we forgive humans for needing iteration. We expect them to get it wrong first, improve with feedback, and learn through debugging. But when AI writes imperfect code, you declare the entire approach fraudulent?
We shouldn't care about flawless one-shot generations. The value is in collapsing the time between idea and execution. If a model can give you a working draft in 3 seconds - even if it's 80% right - that's already a 10x shift in how we build software.
Don't confuse the present with the limit. Eventually, in not that many years, you'll vibe in English, and your AI co-dev will do the rest.