Comment by currymj | Hacker News Reader

Comment by currymj | Hacker News Reader

software is really weird as a test case for understanding AI automation on white collar work.

it seems exceptionally well-suited to AI-based automation because software engineering has already needed to figure out how to efficiently cope with humans who sometimes produce code which may have defects. most obviously automated testing and type systems. also a lot of programming tasks have verifiable solutions so it's also better for training. it seems natural that the most obviously successful AI tools are for coding.

yet the software industry has also been absorbing waves of automation for 70 years. Fortran and COBOL were referred to as "automated programming" and there was a narrative that these new tools would make it easy for non-specialists to program. this time may be different, or it may just be another wave of automation.

i think software has pretty unique properties among white collar jobs, and I would hesitate to draw conclusions about other industries based on AI progress in software engineering.

I had the opposite thought. That it was the most difficult of things to replace with AI, and that the eagerness to do so was driven by non developers who see it as an expensive cost centre that is holding them hostage. Where I work still uses very bad outsourced service desk humans, and almost computer illiterate (and sometimes actually illiterate) manual testers and wages approaching that of a senior developer. Why not them first?

I also don't really care if my job is automated. If it doesn't need doing anymore, why should I want to do it? I will do something else.

The issue is people are assuming 100% automation and job replacement by AI/ML overnight - that is NOT happening in the near future.

Realistically, we are going to see 20-30% reductions in headcount in the near-to-medium term. THIS IS STILL CATASTROPHIC.

A number of earlier stage companies I've funded have already been heavily utilizing automation to simplify code generation or scaffolding/project ops work. They use the cost savings to hire experienced SWEs at high base salaries and are able to hit the same development metrics as they would have if they had a large team of average paid SWEs. On the BDR side, they are using a massive amount of video/audio automation to scale out cold calling or first impressions, so reducing the need to hire teams of BDRs hitting the phones all the time. And finally, they are automating tier 1/2 support ticket responses and communication so reducing the need for teams of support engineers spending time basically respondng to customers with the polite equivalnet of "read the docs".

Basically, a Series A startup that would have had a staff of 50 employees 10 years ago can essentially output the exact same as a Series A startup with a headcount of 20 employees today, and with a tangible path to FCF positivity.

This is a net reduction in jobs, and a significant one at that, because most people just cannot upskill - it's hard.

> A number of earlier stage companies I've funded have already been heavily utilizing automation to simplify code generation or scaffolding/project ops work. They use the cost savings to hire experienced SWEs at high base salaries and are able to hit the same development metrics as they would have if they had a large team of average paid SWEs. On the BDR side, they are using a massive amount of video/audio automation to scale out cold calling or first impressions, so reducing the need to hire teams of BDRs hitting the phones all the time. And finally, they are automating tier 1/2 support ticket responses and communication so reducing the need for teams of support engineers spending time basically respondng to customers with the polite equivalnet of "read the docs".

Impressive.

> This is a net reduction in jobs, and a significant one at that, because most people just cannot upskill - it's hard.

So you lose out on people to do work? That they cannot upskill implies that there are jobs to fill. That seems like an economic void there. If the jobs cannot be filled something else must compensate.

But I see no reason to accept this narrative. In the long run we’re all upskilled out of a job. Our tiny brains can’t keep up. Certainly if something as simple-sounding as code generation and/or scaffolding can reduce headcount by this much. What will full-force AI do then?

Maybe they shouldn’t spend their time chasing that promise of bigger brain job tasks and (maybe even) higher pay (because big IQ means big pay?). Eventually the rent-seeking becomes too naked to ignore. Maybe around the time when the whole operation is maintained by the last twenty or so biggest brains of the lot (survival of the biggest). Then their tasks all get automated. Whose left standing with the spoils? Not the biggest brains.

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