Bounds bounds bounds bounds. The important part for humans seems to be maintaining boundaries for AI. If your well-tested codebase has the tests built thru AI, its probably not going to work.
I think its somewhat telling that they can't share numbers for how they're using it internally. I want to know that Microsoft, the company famous for dog-fooding is using this day in and day out, with success. There's real stuff in there, and my brain has an insanely hard time separating the trillion dollars of hype from the usefulness.
So far, the agent has been used by about 400 GitHub employees in more than 300 our our repositories, and we've merged almost 1,000 pull requests contributed by Copilot.
In the repo where we're building the agent, the agent itself is actually the #5 contributor - so we really are using Copilot coding agent to build Copilot coding agent ;)
(Source: I'm the product lead at GitHub for Copilot coding agent.)
It is difficult to get a man to understand something when his salary depends upon his not understanding it. - Upton Sinclair
Who would've thought (except you) that this would be one of the things that AI would be especially suited for. I don't know what this progression means in the long run. Will good engineers just become 1000x more productive as they manage X number of agents building increasingly complex code (with other agents constantly testing, debugging, refactoring and documenting them) or will we just move to a world where we just have way fewer engineers because there is only a need for so much code.
My view is in between yours: A bit of column A and B in the sense both outcomes to an extent will play out. There will be less engineers but not by the factor of productivity (Jevon's paradox will play out but eventually tap out), there will be even more software especially of the low end, and the ones that are there will be expected to be smarter and work harder for the same or less pay grateful they got a job at all. There will be more "precision and rigor", more keeping up required by workers, but less reward for the workers that perform it. In a capitalist economy it won't be seen as a profession to aspire to anymore by most people.
Given most people don't live to work, and use their career to also finance and pursue other life meanings it won't be viable for most people long term especially when other careers give "more bang for buck" w.r.t effort put into them. The uncertainty in the SWE career that most I know are feeling right now means to newcomers I recommend on the balance of risk/reward its better to go another career path especially for juniors who have a longer runway. To be transparent I want to be wrong, but the risk of this is getting higher now everyday.
i.e. AI is a dream for the capital class, and IMO potentially disastrous for social mobility long term.
Even in the early days of LLM-assisted coding tools, I already know that there will be executives who would said: Let's replace our pool of expensive engineers with a less expensive license. But the only factor that led to this decision is cost comparison. Not quality, not maintenance load, and very much not customer satisfaction.