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You can ask agents to identify and remove cruft. You can ask an agent why something is breaking -- to hypothesize potential causes and test them for validity. I

You can ask agents to identify and remove cruft. You can ask an agent why something is breaking -- to hypothesize potential causes and test them for validity. If you don't understand how something is built, you can ask the agent to give you an overview of the architecture and then dive into whatever part you want to explore more. And it's not like any of your criticisms don't apply to human teams. They also let cruft develop, are confused by breakages, and don't understand the code because everyone on the original team has since left for another company.

renegade-otter 1y ago
Because what we need is not lazy people - we need lazy people with AI? How is this even a justification?
- crazygringo 1y ago
  Sorry, where did "lazy people" come from? Nobody's talking about anybody being lazy.
  - infintropy 1y ago
    I just like that evolution doesnt really care. People can opine on laziness and proper methodology. Its handwaving compared to how things shake out. Nature does select for laziness. The laziest state that can outpace entropy in diverse ways? Ideal selection.
NitpickLawyer 1y ago
> you can ask the agent to give you an overview of the architecture and then dive into whatever part you want to explore more. This is actually a cool use that's being explored more and more. I first saw it in the wiki thing from the devin people, and now google released one as well.
- theshrike79 1y ago
  There's a cool demo from Anthropic: https://www.youtube.com/watch?v=OwMu0pyYZBc https://www.youtube.com/watch?v=OwMu0pyYZBc Where they use Claude to analyse an old (demo) COBOL application. And it understands the context of the files, decrypts the process and even draws graphs to the documentation it creates. I wish I had this 20 years ago when I was consulting and had to jump into really funky client codebases with zero documentation and everything on fire.
flatline 1y ago
Humans are just better at communicating about their process. They will spend hours talking over architectural decisions, implementation issues, writing technical details in commit messages and issue notes, and in this way they not only debug their decisions but socialize knowledge of both the code and the reasons it came to be that way. Communication and collaboration are the real adaptive skills of our species. To the extent AI can aid in those, it will be useful. To the extent it goes off and does everything in a silo, it will ultimately be ignored - much like many developers who attempt this. I do think the primary strengths of genai are more in comprehension and troubleshooting than generating code - so far. These activities play into the collaboration and communication narrative. I would not trust an AI to clean up cruft or refactor a codebase unsupervised. Even if it did an excellent job, who would really know?
- crazygringo 1y ago
  > Humans are just better at communicating about their process. I wish that were true. In my experience, most of the time they're not doing the things you talk about -- major architectural decisions don't get documented anywhere, commit messages give no "why", and the people who the knowledge got socialized to in unrecorded conversations then left the company. If anything, LLM's seem to be far more consistent in documenting the rationales for design decisions, leaving clear comments in code and commit messages, etc. if you ask them to. Unfortunately, humans generally are not better at communicating about their process, in my experience. Most engineers I know enjoy writing code, and hate documenting what they're doing. Git and issue-tracking have helped somewhat, but it's still very often about the "what" and not the "why this way".
  - recitedropper 1y ago
    "major architectural decisions don't get documented anywhere" "commit messages give no "why"" This is so far outside of common industry practices that I don't think your sentiment generalizes. Or perhaps your expectation of what should go in a single commit message is different from the rest of us... LLMs, especially those with reasoning chains, are notoriously bad at explaining their thought process. This isn't vibes, it is empiricism: https://arxiv.org/abs/2305.04388 https://arxiv.org/abs/2305.04388 If you are genuinely working somewhere where the people around you are worse than LLMs at explaining and documenting their thought process, I would looking elsewhere. Can't imagine that is good for one's own development (or sanity).
tyg13 1y ago
Sure, you can ask the agents to "identify and remove cruft" but I never have any confidence that they actually do that reliably. Sometimes it works. Mostly they just burn tokens, in my experience. > And it's not like any of your criticisms don't apply to human teams. Every time the limitations of AI are discussed, we see this unfair standard applied: ideal AI output is compared to the worst human output. We get it, people suck, and sometimes the AI is better. At least the ways that humans screw up are predictable to me. And I rarely find myself in a gaslighting session with my coworkers where I repeatedly have to tell them that they're doing it wrong, only to be met with "oh my, you're so right!" and watch them re-write the same flawed code over and over again.

renegade-otter 1y ago

Because what we need is not lazy people - we need lazy people with AI? How is this even a justification?

crazygringo 1y ago
Sorry, where did "lazy people" come from? Nobody's talking about anybody being lazy.
- infintropy 1y ago
  I just like that evolution doesnt really care. People can opine on laziness and proper methodology. Its handwaving compared to how things shake out. Nature does select for laziness. The laziest state that can outpace entropy in diverse ways? Ideal selection.

NitpickLawyer 1y ago

> you can ask the agent to give you an overview of the architecture and then dive into whatever part you want to explore more. This is actually a cool use that's being explored more and more. I first saw it in the wiki thing from the devin people, and now google released one as well.

theshrike79 1y ago
There's a cool demo from Anthropic: https://www.youtube.com/watch?v=OwMu0pyYZBc https://www.youtube.com/watch?v=OwMu0pyYZBc Where they use Claude to analyse an old (demo) COBOL application. And it understands the context of the files, decrypts the process and even draws graphs to the documentation it creates. I wish I had this 20 years ago when I was consulting and had to jump into really funky client codebases with zero documentation and everything on fire.

flatline 1y ago

Humans are just better at communicating about their process. They will spend hours talking over architectural decisions, implementation issues, writing technical details in commit messages and issue notes, and in this way they not only debug their decisions but socialize knowledge of both the code and the reasons it came to be that way. Communication and collaboration are the real adaptive skills of our species. To the extent AI can aid in those, it will be useful. To the extent it goes off and does everything in a silo, it will ultimately be ignored - much like many developers who attempt this. I do think the primary strengths of genai are more in comprehension and troubleshooting than generating code - so far. These activities play into the collaboration and communication narrative. I would not trust an AI to clean up cruft or refactor a codebase unsupervised. Even if it did an excellent job, who would really know?

crazygringo 1y ago
> Humans are just better at communicating about their process. I wish that were true. In my experience, most of the time they're not doing the things you talk about -- major architectural decisions don't get documented anywhere, commit messages give no "why", and the people who the knowledge got socialized to in unrecorded conversations then left the company. If anything, LLM's seem to be far more consistent in documenting the rationales for design decisions, leaving clear comments in code and commit messages, etc. if you ask them to. Unfortunately, humans generally are not better at communicating about their process, in my experience. Most engineers I know enjoy writing code, and hate documenting what they're doing. Git and issue-tracking have helped somewhat, but it's still very often about the "what" and not the "why this way".
- recitedropper 1y ago
  "major architectural decisions don't get documented anywhere" "commit messages give no "why"" This is so far outside of common industry practices that I don't think your sentiment generalizes. Or perhaps your expectation of what should go in a single commit message is different from the rest of us... LLMs, especially those with reasoning chains, are notoriously bad at explaining their thought process. This isn't vibes, it is empiricism: https://arxiv.org/abs/2305.04388 https://arxiv.org/abs/2305.04388 If you are genuinely working somewhere where the people around you are worse than LLMs at explaining and documenting their thought process, I would looking elsewhere. Can't imagine that is good for one's own development (or sanity).

tyg13 1y ago

Sure, you can ask the agents to "identify and remove cruft" but I never have any confidence that they actually do that reliably. Sometimes it works. Mostly they just burn tokens, in my experience. > And it's not like any of your criticisms don't apply to human teams. Every time the limitations of AI are discussed, we see this unfair standard applied: ideal AI output is compared to the worst human output. We get it, people suck, and sometimes the AI is better. At least the ways that humans screw up are predictable to me. And I rarely find myself in a gaslighting session with my coworkers where I repeatedly have to tell them that they're doing it wrong, only to be met with "oh my, you're so right!" and watch them re-write the same flawed code over and over again.