They don’t want to sell these tools to developers. They want to cut as many layers as possible.
replyWhere I work:
replyDevelopers very rarely blow their limits, except when they're experimenting on purpose.
Most non-developers are out of tokens by the half of the week, and need to use usage credits for the remainder.
To me there is clearly a better target demographic for AI.
I wonder too if in training for long horizon tasks agents become worse team players, good at orchestrating subagents they are trained to use, but worse as an agent within an external multi-agent orchestration system or just in turn-taking with humans. That was my experience with Opus 5 and so far it has been my early experience with Astra as well.
replyI wouldn't be surprised if they are optimising for producing more code, because in the long term, more existing code means they can sell you more tokens to maintain it.
replyThe incentives are certainly extremely strong. I have read hundreds of AI review comments, and I don't think I've ever seen an unprompted suggestion focused on net reducing code or increasing readability.
replySo the AI equivalent of the socially stunted but brilliant researcher?
replyI wonder if we will start using LLMs to translate the output of other LLMs to make it more palatable for humans.
replyso they trained it to be a 10x engineer?
replydeleted
reply> This matches my experience with Astra so far too.
> I think I’m suspecting something is going “wrong” in the training process. The model is greatly rewarded for succeeding on long-horizon tasks, but presumably there is very little punishing going on for “shitty code.”
replyProbably because so many influencers in the space say stupid things like: “it works, right? Why would I spend time reviewing ai generated code?” As if the junior engineer who wrote over engineered complex and sometimes bad code — if they had just done it faster — would somehow be acceptable. wtf?