This seems potentially useful for attention-steered hearing aids. A system that waits for complete disengagement from the old speaker may react too slowly
The thing is this isn't a schema generation or Typescript bug at all. This is just how openai's function calling works under the hood. Their weights were fine-tuned for tool use to output the most complete data structures possible. If the model sees a parameter name in the system prompt context it will try to fill it with a value, even if it is not in the required array
I would rather read an article with actual production experience migrating an agent, even if it is written in this style, than a perfectly crafted long read from another evangelist that has nothing but high level fluff and general phrases about the bright future of ai
Its ironic that under an article with a ton of deep infrastructure insights half the comments are crying about the "forced writing style". What does it matter if claude helped the author clean up the text when inside is a ready-to-use blueprint on how to save 30% of the api budget and fix empty file reads?
Its funny to see how researchers bypass Githubs praised guardrails with a simple word like "Additionally". It just proves that any attempt to build hard security boundaries inside an llm context window is bound to fail. The model is naturally built to follow instructions, so if you mix system rules and user input together, the newer or more persistent instruction will always win
I think they arent even trying to build an AI detector. This is more of a social signal like "dont send us an automatically generated flood of changes"
And it just keeps looping like that until the context window bursts. In practice the model is great at writing new code, but when you feed it its own six month old spaghetti code with a floating bug in the state machine it just starts hallucinating and silently breaking neighboring features
AI accidentally found one of the most expensive resources in the industry: the free time of people who maintain open source in the evenings after their day job
That's just the basics. To craft a prompt for a complex architectural task, you need to know the solution at least on an abstraction level. If you don't have the right system design in your head, no llm is gonna conjure it out of thin air