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0 pointskeeda5mo ago0 comments

> Yes, but I think pre-AI virtually everyone reading this would have been very skeptical about their ability to do so.

That's not quite true: while everybody acknowledged it was folly to measure absolute individual productivity, there were aggregate metrics many in the industry were aligning on like DORA or the SPACE framework, not to mention studies like https://dl.acm.org/doi/abs/10.1145/3540250.3558940

Similarly, many of these AI coding studies do not look at productivity on an individual level at a point of time, but in aggregate and over an extended period of time using a randomized controlled trial. It's not saying Alice is more productive than Bob, it's saying Alice and Bob with AI are on average more productive than themselves without AI.

> They claim that this won't impact quality because of the aforementioned review and their QA process. Do you think that's a realistic assessment? If and on the off chance you think it is, why didn't this happen on a larger scale pre-LLM?

Interestingly, I think something similar did happen pre-LLM at industry-scale! My hypothesis (based on observations when personally involved) is that this is exactly what allowed offshoring to boom. The earliest attempts at offshoring were marked by high-profile disasters that led many to scoff at the whole idea. However companies quickly learned and instituted better processes that basically made failures an exception rather than the norm.

I expand a bit more and draw parallels to coding with AI here: https://news.ycombinator.com/item?id=44944717

> ... as is the fact that LLM generated code is still worse than human generated...

I still don't think that can be assumed as a fact. The few studies I've seen find comparable outcomes, with LLMs actually having a slight edge in some cases, e.g.

- https://arxiv.org/abs/2501.16857

- https://arxiv.org/html/2508.00700v1

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lunar_mycroft5mo ago

> My hypothesis (based on observations when personally involved) is that this is exactly what allowed offshoring to boom.

Offshoring did happen, but if you were correct that only the quality control process impacted final quality, the software industry would have looked something like e.g. garment industry, with basically zero people being paid to actually write software in the first world, and hires from the developing world not requiring much skill. What we actually see is that some offshoring occurred, but it was limited and when it did occur companies tried to hire highly trained professionals in the country they outsourced to, not the cheapest bootcamp dev they could find. That's because the quality of the code at generation does matter, so it becomes a tradeoff between cost and quality.

> I still don't think that can be assumed as a fact. The few studies I've seen find comparable outcomes, with LLMs actually having a slight edge in some cases, e.g.

Anthropic doesn't actually believe in their LLMs as strongly as you do. You know how I can tell? Because they just spent millions acquihiring the Bun team instead of asking Claude to write them a JS runtime (not to mention the many software engineering roles they're advertising on their website). They know that their SOTA LLMs still generate worse code than humans, that they can't completely make up for it in the quality control phase, and that they at the very least can't be confident of that changing in the immediate future.

keedaOP5mo ago

Offshoring wasn't really limited... looking at India as the largest offshoring destination, it is in the double-digit billions annually, about 5 - 10% of the entire Indian GDP, and it was large enough that it raised generations of Indians from lower middle-class to the middle and upper-middle class.

A large part of the success was, to your point, achieved by recruiting highly skilled workers at the client and offshoring ends, but they were a small minority. The vast majority of the workforce was much lower skilled. E.g. at one point the bulk of "software engineers" hired didn't even study computer science! The IT outsourcing giants would come in and recruit entire batches of graduates regardless of their education background. A surprisingly high portion of, say, TCS employees have a degree in something like Mechanical Engineering.

They key strategy was that these high-skilled workers acted as high-leverage points of quality control that were scaled to a much larger force of lower-skilled workers via processes. As the lower strata of workers upskilled over time, they were in turn promoted to lead other projects with lower-skilled workers.

In fact, you see this same dynamic in high-performing software teams, where there is a senior tech lead and a number of more junior engineers. The quality of output depends heavily on the skill-level of the lead rather than the more numerous juniors.

Re: Anthropic, I think we're conflating coding and software engineering. Writing an entire JS runtime is not just coding, it's a software engineering project, and I totally agree that AI cannot do software engineering: https://news.ycombinator.com/item?id=46210907