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The whole premise seems off. The article claims that AI could only ever help with code editing/typing, and not with navigating, understanding the codebase, etc.

The whole premise seems off. The article claims that AI could only ever help with code editing/typing, and not with navigating, understanding the codebase, etc. Which current AIs can already do to some extent. And therefore, according to major-citation-needed pie chart, editing code is only 5% of the job, thus AI will always and forever only be able to save us 5% or less of our time. Seems pretty wooly.

ChatGTP 4y ago
Let's not pretend that there isn't some truth to software complexity though, and let's not pretend that the faster we can copy pasta solutions into codebases using "AI", the more complexity we'll likely be introducing. A 10x productivity increase could introduce a 10x+ complexity increase. One reason I think ChatGPT is so impressive is because it's remixing and suggesting code, from already well structured code bases, functions etc, calling on well designed libraries etc. My gut feeling is that MS have allowed all of Github to be "sampled", which is why the code ChatGPT is serving up seems to "familiar". Unless these models start to actually improve the code, ie suggest better, less complicated paths and architectures, there is a chance software will go backwards to the point where just getting LLMs to pattern match a change into a 500,000 long line codebase of auto-generated, randomized solutions stops working, then of course, we'll need a "bigger" model to grok it all, explain what the code is doing etc. We could call it "drift" or similar, but I think the fact we write code that is easy to understand for others, including LLMs is actually a feature and not a bug. Anything "cognitive" would have to agree at some stage, unless we have unlimited cognition, for every code change available, which is honestly a fantasy at this stage. I might be wrong, and I'm happy to be wrong, but this is probably the best time in history to be using auto-completion for coding. There's plenty of well thought out, nice training data available, I don't think that will hold water if we just get copy-pasting, neglect using nice libraries etc. One interesting example I saw recently was someone showed me how they were using ChatGPT-4 to check their code for vulnerabilities, it actually did quite well, albeit it was very basic / best practices stuff everyone should know that needed fixing. Then i watched someone else in a different context, use it to generate code, that was vulnerable and susceptible to the same problems. We could automate the vulnerability checking (many people already do), but then it becomes an interesting back and fourth between systems writing and fixing code, at some stage it probably becomes inefficient to do this in it's own right. Brute forcing.
- euroderf 4y ago
  Your first four paragraphs make me wonder if A.I. might nudge developers into converging onto "best algorithms" - and to a possibly lesser extent, onto "best practices". Or is real-world code an impossibly complex algorithm soup ?
  - ChatGTP 4y ago
    It's an interesting problem to consider I guess.
- namaria 4y ago
  I believe people are coming to these with two world views: to some, code is just something you feed into the computer to get a result. This mental model lends itself to getting impressed by these new chatbots and seeing them as a helping hand. Some other people see code as a way to communicate about systems specifications. This is the foundation of collaboration on complex software products. In this arena, lowering entry barriers and the cost of writing code will reduce quality and introduce complex, hard to debug failure modes.
greybeard228 4y ago
@QuadrupleA the paragraph below the chart you referenced has a link to a post I did on that subject which does link to the study it is from if you are interested.

ChatGTP 4y ago

Let's not pretend that there isn't some truth to software complexity though, and let's not pretend that the faster we can copy pasta solutions into codebases using "AI", the more complexity we'll likely be introducing. A 10x productivity increase could introduce a 10x+ complexity increase. One reason I think ChatGPT is so impressive is because it's remixing and suggesting code, from already well structured code bases, functions etc, calling on well designed libraries etc. My gut feeling is that MS have allowed all of Github to be "sampled", which is why the code ChatGPT is serving up seems to "familiar". Unless these models start to actually improve the code, ie suggest better, less complicated paths and architectures, there is a chance software will go backwards to the point where just getting LLMs to pattern match a change into a 500,000 long line codebase of auto-generated, randomized solutions stops working, then of course, we'll need a "bigger" model to grok it all, explain what the code is doing etc. We could call it "drift" or similar, but I think the fact we write code that is easy to understand for others, including LLMs is actually a feature and not a bug. Anything "cognitive" would have to agree at some stage, unless we have unlimited cognition, for every code change available, which is honestly a fantasy at this stage. I might be wrong, and I'm happy to be wrong, but this is probably the best time in history to be using auto-completion for coding. There's plenty of well thought out, nice training data available, I don't think that will hold water if we just get copy-pasting, neglect using nice libraries etc. One interesting example I saw recently was someone showed me how they were using ChatGPT-4 to check their code for vulnerabilities, it actually did quite well, albeit it was very basic / best practices stuff everyone should know that needed fixing. Then i watched someone else in a different context, use it to generate code, that was vulnerable and susceptible to the same problems. We could automate the vulnerability checking (many people already do), but then it becomes an interesting back and fourth between systems writing and fixing code, at some stage it probably becomes inefficient to do this in it's own right. Brute forcing.

euroderf 4y ago
Your first four paragraphs make me wonder if A.I. might nudge developers into converging onto "best algorithms" - and to a possibly lesser extent, onto "best practices". Or is real-world code an impossibly complex algorithm soup ?
- ChatGTP 4y ago
  It's an interesting problem to consider I guess.
namaria 4y ago
I believe people are coming to these with two world views: to some, code is just something you feed into the computer to get a result. This mental model lends itself to getting impressed by these new chatbots and seeing them as a helping hand. Some other people see code as a way to communicate about systems specifications. This is the foundation of collaboration on complex software products. In this arena, lowering entry barriers and the cost of writing code will reduce quality and introduce complex, hard to debug failure modes.

greybeard228 4y ago

@QuadrupleA the paragraph below the chart you referenced has a link to a post I did on that subject which does link to the study it is from if you are interested.