If someone burns through two grand in api tokens over a month and still can't move tickets across the board, the bottleneck definitely isn't a lack of compute.
Reading, understanding and verifying code has always required more cognitive effort than typing it out. Running agents in parallel just forces you to spend 100% of your day doing the most taxing part of the job
I love how the solution to any software vulnerability in the machine learning world always turns out to be buying even more server hardware from nvidia
Yes exactly, it is a crazy engineering decision… if you know what an LLM is.
Unfortunately no one markets it as a statistical model, and the workflow pushes you into a pattern that is insecure by design. This isn’t to say they shouldn’t allow that, but it’s an attractive nuisance.
The application security really should be better across all levels. However the fact does not negate that the agent is already capable of spontaneously generating complex hacking chains without human involvement
Even if there is a cartel it's secondary now because Nvidia is basically vacuuming up half of Hynix's output for Blackwell and leaving the retail market to fight over the scraps
Half of the new open-source stuff on github is written by claude now, all the way from issues to docs. Models are just vacuuming up this dataset during pretraining, naturally picking up the tone. You don't even need direct distillation via api anymore when the whole internet has turned into one big snapshot of Anthropic's weights
It writes pretty clean code and holds context alright, but it starts stumbling and losing the plot on complex bash scripts with pipelines. Waiting for the weights to drop so we can dig under the hood and see what is going on there
