[JumpCrisscross]

> you are missing a lot of "ifs" in that hypothetical

The big one being I'm not assuming AGI. Low-level coding tasks, the kind frequently outsourced, are within the realm of being competitive with offshoring with known methods. My point is we don't need to assume AGI for these valuations to make sense.

[HarHarVeryFunny]

Current AI coding assistants are best at writing functions or adding minor features to an existing code base. They are not agentic systems that can develop an entire solution from scratch given a specification, which in my experience is more typcical of the work that is being outsourced. AI is a tool, whose full-cycle productivity benefit seems questionable. It is not a replacement for a human.

[JumpCrisscross]

> they are not agentic systems that can develop an entire solution from scratch given a specification, which in my experience is more typcical of the work that is being outsourced

If there is one domain where we're seeing tangible progress from AI, it's in working towards this goal. Difficult projects aren't in scope. But most tech, especially most tech branded IT, is not difficult. Everyone doesn't need an inventory or customer-complaint system designed from scratch. Current AI is good at cutting through that cruft.

[ehnto]

There have been off the shelf solutions for so many common software use cases, for decades now. I think the reason we still see so much custom software is that the devil is always in the details, and strict details are not an LLMs strong suit.

LLMs are in my opinion hamstrung at the starting gate in regards to replacing software teams, as they would need to be able to understand complex business requirements perfectly, which we know they cannot. Humans can't either. It takes a business requirements/integration logic/code generation pipeline and I think the industry is focused on code generation and not that integration step.

I think there needs to be a re-imaging of how software is built by and for interaction with AI if it were to ever take over from human software teams, rather than trying to get AI to reflect what humans do.

[netdevnet]

This, code is written by humans for humans. LLMs cannot compete no matter how much data you throw at them. A world in which software is written by AI will likely won't be code that will be readable by humans. And that is dangerous for anything where people's health, privacy, finances or security is involved

[senko]

There are a number of agentic systems that can develop more complex solutions. Just a few off the top of my head: Pythagora, Devin, OpenHands, Fume, Tusk, Replit, Codebuff, Vly. I'm sure I've missed a bunch.

Are they good enough to replace a human yet? Questionable[0], but they are improving.

[0] You wouldn't believe how low the outsourcing contractors' quality can go. Easily surpassed by current AI systems :) That's a very low bar tho.

[netdevnet]

I don't know what's your experience with outsourcing. But people outsource full projects not the writing of a couple of methods. With LLMs still unable to fully understand relatively simple stuff, you can't expect them to deliver a project whose specification (like most software projects) contains ambiguities that only an experienced dev can detect and ask deep questions about the intention and purpose of the project. LLMs are nowhere near that. To be able to handle external uncertainty and turn it into certainty, to explain why technical decisions were made, to understand the purpose of a project and how it matches the project. To handle the overall uncertainties of writing code with other's people's code. All this is stuff outsourced teams do well. But LLMs won't be anywhere near good for at least a decade. I am calling it