The pix2code paper is interesting, but it doesn't really answer the question of translating the UI requirements into the corresponding "business logic" - it's limited to producing the code that manipulates the "surface" elements, so to speak. The real challenge I think for an AGI is translating something like, "This button shows green, if the user has previously scored 10 or higher on the previous 5 tests, which have all been taken in the previous 6 weeks," into code.

Then there's the problem of edge cases - in this case, what if the user has not had an account for more than 6 weeks but has met the other conditions? Now the AGI has to detect that context and formulate the question back to the developer.

The "code will eat your coding job" hype sounds a lot like "we'll have self-driving cars all over the country by 2000" hype (yes, that hype did exist back then,) or going further back, "All of AI is done, we just need a few more decision rules" hype back in the seventies.

For sure, many coding frameworks are a lot simpler now than they were two decades ago, and yes, I think it has meant many aspects of digitized services are now much cheaper. You can build a Wix website for yourself, or a Shopify e-business, without paying a developer, which you needed to do in the year 2000. But the consequent growth in digital businesses has led to induced demand for more developers, as businesses constantly test the edges of these "no-code" services.

I would say we have reached some amount of saturation already. Anec-datally, it seems that if you segmented salaries by experience, you might find some amount of decline or stagnation in the lower levels of experience relative to a decade ago. So in that sense, the original point has some valence, but I don't think it has anything to do with "AI"

Assuming pix2code really did automate away traditional UI work, the development effort would then move to the next subdomain (e.g. a sales bot, etc).

I suspect as long as you're willing to learn and are competent, you should have a job until the final effort of a general AI self-learning programmer.

I'm also sceptical about pix2code, but the point is that domain specific automation could consevably reduce the number of overall jobs. The cost of switching domains is also non negligible.

The question with domain specific automation (and one of my takeaways from the article) isn't whether or not you'll have a job, but if the effort your put into getting your current job is worthwhile.

I think the total number of jobs (programming + other) that humans can do economically might go down over time. Programmers can usually pickup the next ambitious project (e.g. a sales bot) when the old domain is no longer profitable.

I think Bartosz is saying that Math and Category theory is useful to learn because it works in a number of subdomains. It can help keep the domain switching cost down somewhat.