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0 pointsAgentlien4mo ago0 comments

The more I hear about other developers' work, the more varied it seems. I've had a few different roles, from one programmer in a huge org to lead programmer in a small team, with a few stints of technical expert in-between. For each the kind of work I do most has varied a lot, but it's never been mostly about "clarifying requirements". As a grunt worker I mostly just wrote and tested code. As a lead I spent most time mentoring, reviewing code, or in meetings. These days I spend most of my time debugging issues and staring at graphics debugger captures.

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oblio4mo ago

> As a lead I spent most time

> mentoring

Clarifying either business or technical requirements for newer or junior hires.

> reviewing code

See mentoring.

> or in meetings

So clarifying requirements from/for other teams, including scope, purely financial or technical concerns, etc.

Rephrase "clarifying requirements" to "human oriented aspects of software engineering".

Plus, based on the graphics debugger part of your comment, you're a game developer (or at least adjacent). That's a different world. Most software developers are line of business developers (pharmaceutical, healthcare, automotive, etc) or generalists in big tech companies that have to navigate very complex social environments. In both places, developers that are just heads down in code tend not to do well long term.

falcor844mo ago

> human oriented aspects

The irony is of course that humans in general and software professionals in particular (myself definitely included) notoriously struggle with communication, whereas RLHF is literally optimizing LLMs for clear communication. Why wouldn't you expect an AI that's both a superhuman coder and a superhuman communicator to be decent at translating between human requirements and code?

oblio4mo ago

> Why wouldn't you expect an AI that's both a superhuman coder and a superhuman communicator to be decent at translating between human requirements and code?

At this point LLMs are a superhuman nothing, except in terms of volume, which is a standard computer thing ("To err is human, but to really foul things up you need a computer" - a quote from 60 years ago).

LLMs are fast, reasonably flexible, but at the moment they don't really raise the ceiling in terms of quality, which is what I would define as "superhuman".

They are comparatively cheaper than humans and volume matters ("quantity has a quality all its own" - speaking of quotes). But I'm fairly sure that superhuman to most people means "Superman", not 1 trillion ants :-)

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oblio4mo ago

> As a lead I spent most time

> mentoring

Clarifying either business or technical requirements for newer or junior hires.

> reviewing code

See mentoring.

> or in meetings

So clarifying requirements from/for other teams, including scope, purely financial or technical concerns, etc.

Rephrase "clarifying requirements" to "human oriented aspects of software engineering".

falcor844mo ago

> human oriented aspects

oblio4mo ago

> Why wouldn't you expect an AI that's both a superhuman coder and a superhuman communicator to be decent at translating between human requirements and code?

LLMs are fast, reasonably flexible, but at the moment they don't really raise the ceiling in terms of quality, which is what I would define as "superhuman".

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