We need 70% less coders as the AI handles most of the coding

The problem with the validation part is that the human has to go through all the code written by AI. Guess what, understanding someone's code takes almost as much effort as writing the code yourself. Therefore you require just about the same amount of human beings verify AI's code.

This is not the first time programmers became more efficient. We've had that happen before; usually because of new languages, tools, and other things that help people become more productive. AI is just another productivity enhancing tool.

Some studies suggest that the lines of codes produced per time unit is more or less constant across different languages. What matters is what those lines do. If you are programming in assembly, it's going to take ages of very verbose programming to get anything done. Do the same in Haskell and you might reduce it to a couple of lines of code.

Based on what happened in the past, we might expect programming work to outgrow the efficiency gains. That's what has happened every time there was a step change reduction in cost for producing software. The community of developers keeps expanding and isn't shrinking.

This is an earnings call, so take it with a grain of salt. There's a strong incentive to represent expenses as low as possible.

Most coding is not rocket science, just drudgery. Still, 7/10 implies some very junior level tasks.

What I don't think the HN bubble is fully familiar with is the fact that probably 70% of programming happening today is boring low paid drudgery (or maybe 50-90%). It's creating dashboards in BI tools, it's tweaking Wordpress themes, it's writing custom business processes in ABAP for SAP deployments, or it's 3-10 engineers doing the work of 1 so that a outsourcing company can bulk up its bills.

This is the sort of work that AI is coming for. It's low impact, low effort, low paid, and importantly it doesn't get automated (often). This means there is a lot of low hanging fruit for automation, whether that's by regular tooling or LLMs.

On the other hand, if you're a highly paid software engineer, it's likely you're already working with highly automated and abstracted systems, so there's much less opportunity for LLMs. If your deployment process is a Word doc specifying the 120 steps you have to run in bash to deploy that takes 1 eng day, that's going to be automated, but if you're git-pushing and having Kubernetes roll it out in your CI/CD flow, automation has already raised the level of abstraction that you need to work at and there are fewer opportunities.

Yes there's Copilot/etc which will reduce boilerplate, but the only way a company achieves "70% less coders" is by wholesale automation of large parts of their process that must be horribly basic already.