This is obviously not true, starting with the AI companies themselves.
It's like the old saying "half of all advertising doesn't work; we just don't which half that is." Some organizations are having great results, while some are not. From the multiple dev podcasts I've listened to by AI skeptics have had a lightbulb moment where they get AI is where everything is headed.
This is well known I thought, as even the people who build the AIs we use talk about this and acknowledge their limitations.
If true, could this explain why Anthropics APIs are less reliable than Gemini's? (I've never gotten a service overloaded response from Google like I did from Anthropic)
My current understanding (based on this text and other sources) is:
- There exist some teams at Anthropic where around 90% of lines of code that get merged are written by AI, but this is a minority of teams.
- The average over all of Anthropic for lines of merged code written by AI is much less than 90%, more like 50%.
They're Google, they out-scale everyone. They run more than 1.3 quadrillion tokens per month through LLMs!
Also, the quality of production ready code is often highly exaggerated.
What I mean more is that as soon as the task becomes even moderately sized, these things fail hard
I think the new one is. I could be the fool and be proven wrong though.
these agents are not up to the task of writing production level code at any meaningful scale
looking forward to high paying gigs to go in and clean up after people take them too far and the hype cycle fades
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I recommend the opposite, work on custom agents so you have a better understanding of how these things work and fail. Get deep in the code to understand how context and values flow and get presented within the system.