I find it strange that the industry hasn't converged in at least somewhat standardized format, but I guess despite all the progress we're still in the very early days...
This is one of the first tech waves where I feel like I'm on the very very groundfloor for a lot of exploration and it only feels like people have been paying closer attention in the last year. I can't imagine too many 'standard' standards becoming a standard that quickly.
It's new enough that Google seems to be throwing pasta against the wall and seeing what products and protocols stick. Antigravity for example seems too early to me, I think they just came out with another type of orchestrator, but the whole field seems to be exploring at the same time.
Everyone and their uncle is making an orchestrator now! I take a very cautious approach lately where I haven't been loading up my tools like agents, ides, browsers, phones with too much extra stuff because as soon as I switch something or something new comes out that doesn't support something I built a workflow around the tool either becomes inaccessible to me, or now a bigger learning curve than I have the patience for.
I've been a big proponent of trying to get all these things working locally for myself (I need to bite the bullet on some beefy video cards finally), and even just getting tool calls to work with some qwen models to be so counterintuitive.
I know this is getting off-topic, but is anybody working on more direct tool calling?
LLMs are based on neural networks, so one could create an interface where activating certain neurons triggers tool calls, with other neurons encoding the inputs; another set of neurons could be triggered by the tokenized result from the tool call.
Currently, the lack of separation between data and metadata is a security nightmare, which enables prompt injection. And yet all I've seen done about is are workarounds.
I would guess that lack of standardization of what tools are provided by different types of agent (e.g. coding agent vs "claw agent") is as much of a problem as the differences in syntax, since the ideal case would be for a model to be trained end-to-end for use with a specific agent and set of tools, as I believe Anthropic do. Any agent interacting with a model that wasn't specifically trained to work with that agent/toolset is going to be at a disadvantage.
Nevermark•3h ago