101–110 of 163 posts
And programmers in Silicon Valley or Seattle make tons more than in Oklahoma.
Earlier quoted context omitted.
>they've only solved "what you boss thinks software engineering is". Which is why bosses are excited but engineers are not, because subpar LLMs will be used to justify firing actual engineers and replace them with fresh college grads tasked to work with a code bot, because the bosses fundamentally think that is enough.
Then those projects will fail and they won't do that anymore. Or they'll succeed and engineers will have to find harder problems to solve. If a new grad + LLM can do task X about as well as an experienced engineer can, then the experienced engineer will have to find other harder problems to solve. Personally I think labor efficiency is good; why waste your labor on easy/solved problems?
The experienced engineer also gets an LLM though
Comment here seem to largely miss the point of the article, which isn't saying that nobody will employ software engineers. It is saying that instead of the current model of: 1 very highly compensated staff+ engineer 4 highly compensated senior engineers 4 pretty well-compensated mid-level engineers 2 decently compensated junior engineers The future might look like: 1 yet-more-highly-compensated staff+ engineer who sp…
The unintuitive thing about software engineering is that low-level implementation and high-level architecture are both equally sensitive to quality of talent (and equally impact your product quality and business outcomes) because every line of code is a business decision. That's a big reason why even entry-level SWE talent costs so much. There is no paralegal-level work in software - it's been automated away.
Earlier quoted context omitted.
Then those projects will fail and they won't do that anymore. Or they'll succeed and engineers will have to find harder problems to solve. If a new grad + LLM can do task X about as well as an experienced engineer can, then the experienced engineer will have to find other harder problems to solve. Personally I think labor efficiency is good; why waste your labor on easy/solved problems?
> then the experienced engineer will have to find other harder problems to solve. The experienced engineer also gets an LLM though
Say experienced engineer Edna was working on a project and the new grad Nelson replaced her because he was cheaper and about as good if both have LLMs, i.e.,
Edna + LLM ≈ Nelson + LLM
even though
Edna >> Nelson.
So Edna needs to find a project to work on where LLMs don't equalize her arbitrage, i.e.,
Edna + LLM >> Nelson + LLM
and Nelson needs one where
Nelson + LLM >> LLM.
There is research [1] that suggests using GPS navigation could impact your brain function negatively. I wonder how this code generation “assistant” will impact the coding skills of its users in long term. As for the LLMs, stochastic parroting (hallucination), which is inherent to its design, makes it untrustworthy for precision work. Maybe some other architecture will prove more useful. LLMs can generate BS authorita…
I just tried ChatGPT today after weeks of hype on Twitter, and I was surprised to NOT be impressed? First I tried it on a bunch of programming topics -- it definitely gets in the right ballpark, but then the details are frequently wrong. I asked which languages have the F# |> operator, and it told me that OCaml, Elixir, Haskell and Scala do. 2 of them are correct, and 2 appeared wrong, so I googled it. After Googling…
There is research [1] that suggests using GPS navigation could impact your brain function negatively. I wonder how this code generation “assistant” will impact the coding skills of its users in long term. As for the LLMs, stochastic parroting (hallucination), which is inherent to its design, makes it untrustworthy for precision work. Maybe some other architecture will prove more useful. LLMs can generate BS authorita…
I wonder how code completion and syntax highlighting have altered the brains of programmers negatively as well.
Thinking of instead of requiring 20 people team, now you can well function with like 10 people.
Earlier quoted context omitted.
I just tried ChatGPT today after weeks of hype on Twitter, and I was surprised to NOT be impressed? First I tried it on a bunch of programming topics -- it definitely gets in the right ballpark, but then the details are frequently wrong. I asked which languages have the F# |> operator, and it told me that OCaml, Elixir, Haskell and Scala do. 2 of them are correct, and 2 appeared wrong, so I googled it. After Googling…
That vibes with the images from what I saw with Dall-E. The rendering/styling was superb, however, the logic and scene understanding were toddler-like. Still impressive, but if you had a picture with dogs sometimes a dog head would be pasted on top at the wrong angle. Confabulation is a great term for it IMHO.
But I can't see how people aren't impressed, we couldn't do this a few years ago, and surely we will build on top of this in coming years.
This post is way to bullish on ChatGPT for coding, and underestimates how big the gap is between ChatGPT and a mid level FANG eng. ChatGPT is very impressive in what it can do, but if you deviate problem statements even a little bit from what it's seen before, it completely fails. Just an example try asking it to write Battleship in Python. It does very well. But then, try changing the rules a bit, and adding some re…
Have it give you a list of functions needed to write battleship.
Then have it write the classes.
Then set the rules.
Then have it write a GUI etc.
You'll have a much more successful encounter that way.
There is research [1] that suggests using GPS navigation could impact your brain function negatively. I wonder how this code generation “assistant” will impact the coding skills of its users in long term. As for the LLMs, stochastic parroting (hallucination), which is inherent to its design, makes it untrustworthy for precision work. Maybe some other architecture will prove more useful. LLMs can generate BS authorita…
I just tried ChatGPT today after weeks of hype on Twitter, and I was surprised to NOT be impressed? First I tried it on a bunch of programming topics -- it definitely gets in the right ballpark, but then the details are frequently wrong. I asked which languages have the F# |> operator, and it told me that OCaml, Elixir, Haskell and Scala do. 2 of them are correct, and 2 appeared wrong, so I googled it. After Googling…
- taking point form, or messy notes, and converting it to full sentences/paragraphs. Useful for things like writing blurbs, longer emails, proposals. Naturally, it does veer towards cliche, so you kind of have to massage it back after.
- getting a bash script started in the right direction. I'm always fuzzy on bash syntax because I don't use it all the time. ChatGPT will usually screw up some details, but those can be fixed
- getting a general overview of a new topic area like a new software library, or say a historical period