[siliconc0w]

People don't really understand that non-trivial software development isn't even 50% coding. The coding step is generally the 'easiest' part and given to Junior developers. In a large org most product changes span multiple systems and human operations. Seniors and even mid-level generally spend most of their figuring out how to shape the local priorities into a new arrangement of the existing cybernetic entity and then getting buy-in on that new vision given these other teams have their own priorities.

This naturally involves a lot of tradeoffs and politics - senior engineers know to avoid adding 'weight' to their airframes and fight hard to avoid adding scope to the systems they're responsible for or divergence from their intended direction of travel. So compromises have to be struck or escalations to management to choose between priorities have to play out.

Maybe AI solves that as well but that is a lot more difficult lift.

[fastball]

LLMs mostly only being code-writers was true a year ago, but it is not true now. Now they are tool-callers, which means a coding agent can effectively: run lints/typechecks/tests (and fix resulting errors), dig into observability platforms to identify root cause of isses (e.g. on Sentry or similar), run benchmarks to identify slow code / hot paths, keep systems up to date by reading migration docs (and applying them) for new majors of consumed libs, etc.

So sure, if you have none of these things set up to back-pressure agents and help them better understand the system, then they will just be dumb LLM code writers. But you can definitely go a lot further than that with the improvements that are rapidly happening to models and harnesses.

[kawaiikouhai]

uh. I think code-writing is just colloquial for "low level implementation details".

What he's pointing at is

1. LLMs have no social pull. Thus all the anti-AI outrage (LLMs cant defend themselves)

2. AI is shit at expert-lvl planning and higher level stuff (vision, architecture).