Ask HN: Will AI put programmers our of work?

> The actual difference is that when shown a picture and told "this is a cat", humans already know what to look for.

Yes exactly. You’ll look for 4 legs, a tail, pointy ears and graceful movement. All of that is data you’ve registered by your (primarily one) senses (sensors). You’re receiving more data, and processing it faster, than a program.

Humans are fundamentally pattern matchers, and we’re great at it. What you call concept I call pattern.

Well, I am in my 70s so job security is not really anything I think about.

Funny, but about 35 years ago I blocked my boss’s boss from buying a company that wrote an “AI coding tool”. I change my mind about things and what I found ridiculously simple and un-useful 35 years ago, is very different than Copilot.

I don’t think it takes a lot of imagination to fully conceptualize how much AI tools will change knowledge work.

I have been a paid AI practitioner since 1982 and I find it exciting how fast the field is now progressing. I worked as a consultant at Google in 2013 with their Knowledge Graph and that opened my eyes to the possibilities of so much structured and organized (they had a very good Ontology team) knowledge. Six years ago I managed a deep learning team at Capital One and mostly because of the strong team, I was surprised how effective deep learning is for practical problems.

One last example: in the 1980s I spent a fair amount of time trying to write code manually for anaphora resolution - a problem that BERT models now solve “simply.”

Agreed. The mark of a senior developer is their ability to decouple concepts and synthesize concepts appropriately depending on the context.

You need to have highly developed critical thinking skills in order to be able to formulate appropriate solutions to problems. What a developer does isn't so different from what an entrepreneur does; they spend most of their time explaining their vision and goals; the difference is that the developer's vision and goals are much more granular and detailed.

I remain unconvinced, there's a huge swathe of legacy industries that the pandemic showed up for being woefully stuck in the past - with "digitalisation" being a buzzwords thrown around during 2020-2021 for older industries that thought working in the 21st century entailed emailing CSVs to each other, working on physical desktops.

I don't think these types of slow moving companies will be the ones to leap frog by jumping all in on AI, moreover I believe the TAM for software development is still growing strongly, AND I'm actually quite interested what happens to the nature of work 10-20 years down the line when most of today's kids who will be able to sort of code and become hybrid workers (to how traders went from shouting in a floor to being quite numeric, or accountants went from physical books to excel).

Tldr my bet is that AI might displace labour but not lead to a net reduction of software labour demand in the next 10-20 years at least

I'm working at a startup's engineering & product team as an engineer. I think it's not fundamentally different from how most software engineers work.

We work on:

- The why: business/leadership, and to some extent, product determines key goals (KPIs, OKRs etc.) and markets we are addressing. Us engineers are only informed parties here.

- The what: product, and to some extent, engineering determines which features to build or improve to attain these goals in a user-friendly and sustainable way. We create projects and design sketches, assign time constraints to them.

- The how: engineering, and to some extent, product ships these features in a maintainable, scalable, performant and supportable way without disrupting existing user experience.

A very large part of this work involves creative processes and logical reasoning about business, UX, software engineering problems. (Of course, that's why I love it :))

Only a tiny amount of this work is "writing boilerplate code" or copying code from Stackoverflow - which ChatGPT is presumed to automate.

Of course, more senior engineers are faster at writing boilerplate, but their speed mostly comes from 1) knowing the existing codebase 2) using the right tools & abstractions.

Moreover, most of the risk involved in the process is not the time taken to write boilerplate i.e. working on something for too long - but rather working on the wrong thing, or doing an implementation that's too slow or hard to maintain (change, test, fix, extend, reason about).

All in all, when I think about software engineering from this perspective, I don't see AI automating it away anytime soon.

I could, though imagine AI being your TDD coder companion. You write some unit or acceptance tests for a service module and the AI generates the code for it. You'd still need to thoroughly review and test the code though. This would work well for basic CRUD/boilerplate modules, but not for anything involving business logic.

Nevertheless, this would still remain just a small part of a software engineer's work, in my opinion. What do you think?