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IMHO, review is a misnomer for where software engineering is going. I'm not sure where we are going, but review implies less responsibility for the outcome. Bu

IMHO, review is a misnomer for where software engineering is going. I'm not sure where we are going, but review implies less responsibility for the outcome. But I do think that we will have less depth of knowledge of the underlying processes. That's the point of having a machine do it. I expect this, however, to be a good trend: the systems will need to be up to a task before it makes sense to rely on them.

reacharavindh 2y ago
This is how progress (in developer productivity) has always been made. We coded in assembler, then used macros, then a language like C, Fortran, then more of Java/Go/Puthon/Rust/Ruby et al. A developer writing a for loop over a list in Python need to necessarily know about linked lists and memory patterns because Python takes care of it. This frees up that developer from abstracted details and think one level closer to the problem at a higher speed. LLMs _can_ be a good tool under the right hands. They certainly have some ways to become a reliable assistant. I suppose in the way of LLMs, they need better training before they can get there.
- discreteevent 2y ago
  > We coded in assembler, then used macros, then a language like C, Fortran, then more of Java/Go/Puthon/Rust/Ruby et al. The difference is that: 1) All of those things are deterministic [1] 2) In all of those cases I can debug at the level of the abstraction. [1] Meaning: Do exactly what I say. Don't make it up.
  - CoastalCoder 2y ago
    I agree with your overall point. In a certain sense I'd say optimizing compilers aren't deterministic: The same source code can produce different object code, depending on data and algorithms into which a typical programmer has little insight.
    - vitiral 2y ago
      Being a bit pedantic. Globally but not locally deterministic
      - shrimp_emoji 2y ago
        Your brain's not deterministic.
    - kibwen 2y ago
      Crucially, optimizers are supposed to be semantics-preserving, and if they aren't that's considered a major problem.
  - deleted 2y ago
    [deleted]

reacharavindh 2y ago

This is how progress (in developer productivity) has always been made. We coded in assembler, then used macros, then a language like C, Fortran, then more of Java/Go/Puthon/Rust/Ruby et al. A developer writing a for loop over a list in Python need to necessarily know about linked lists and memory patterns because Python takes care of it. This frees up that developer from abstracted details and think one level closer to the problem at a higher speed. LLMs _can_ be a good tool under the right hands. They certainly have some ways to become a reliable assistant. I suppose in the way of LLMs, they need better training before they can get there.

discreteevent 2y ago
> We coded in assembler, then used macros, then a language like C, Fortran, then more of Java/Go/Puthon/Rust/Ruby et al. The difference is that: 1) All of those things are deterministic [1] 2) In all of those cases I can debug at the level of the abstraction. [1] Meaning: Do exactly what I say. Don't make it up.
- CoastalCoder 2y ago
  I agree with your overall point. In a certain sense I'd say optimizing compilers aren't deterministic: The same source code can produce different object code, depending on data and algorithms into which a typical programmer has little insight.
  - vitiral 2y ago
    Being a bit pedantic. Globally but not locally deterministic
    - shrimp_emoji 2y ago
      Your brain's not deterministic.
  - kibwen 2y ago
    Crucially, optimizers are supposed to be semantics-preserving, and if they aren't that's considered a major problem.
- deleted 2y ago
  [deleted]