In my opinion it’s to some degree an artifact of immature and/or rapidly changing technology. Basically not many know what the best approach is, all the use cases aren’t well understood, and things are changing so rapidly they’re basically just creating interfaces around everything so you can change flow in and out of LLMs any way you may desire.
Some paths are emerging popular, but in a lot of cases we’re still not sure even these are the long term paths that will remain. It doesn’t help that there’s not a good taxonomy (that I’m aware of) to define and organize the different approaches out there. “Agent” for example is a highly overloaded term that means a lot of things and even in this space, agents mean different things to different groups.
I liken the discovery/invention of LLMs to the discovery/invention of the electric motor - it's easy to take things like cars, drills, fans, pumps etc. for granted now, and all of the ergonomics and standards around them seem obvious in this era, but it took quite a while to go from "we can put power in this thing and it spins" to the state we're in today.
For LLMs, we're just about at the stage where we've realized we can jam a sharp thing in the spinny part and use it to cut things. The race is on not only to improve the motors (models) themselves, but to invent ways of holding and manipulating and taking advantage of this fundamental thing that feel so natural that they seem obvious in hindsight.
None of them matter that much. They're all just ways to bring in context. Think of them as conveniences.
Tools are useful so the AI can execute commands, but beyond that it's just ways to help you build the context for your prompt. Either pulling in premade prompts that provides certain instructions or documentation, or providing more specialized tools for the model to use along with instructions on using those tools.
All marketing names for APIs and prompts. IMO you don't need to even try to follow, because there's nothing inherently new or innovative about any of this.
In my opinion it’s to some degree an artifact of immature and/or rapidly changing technology. Basically not many know what the best approach is, all the use cases aren’t well understood, and things are changing so rapidly they’re basically just creating interfaces around everything so you can change flow in and out of LLMs any way you may desire.
Some paths are emerging popular, but in a lot of cases we’re still not sure even these are the long term paths that will remain. It doesn’t help that there’s not a good taxonomy (that I’m aware of) to define and organize the different approaches out there. “Agent” for example is a highly overloaded term that means a lot of things and even in this space, agents mean different things to different groups.
I liken the discovery/invention of LLMs to the discovery/invention of the electric motor - it's easy to take things like cars, drills, fans, pumps etc. for granted now, and all of the ergonomics and standards around them seem obvious in this era, but it took quite a while to go from "we can put power in this thing and it spins" to the state we're in today.
For LLMs, we're just about at the stage where we've realized we can jam a sharp thing in the spinny part and use it to cut things. The race is on not only to improve the motors (models) themselves, but to invent ways of holding and manipulating and taking advantage of this fundamental thing that feel so natural that they seem obvious in hindsight.
None of them matter that much. They're all just ways to bring in context. Think of them as conveniences.
Tools are useful so the AI can execute commands, but beyond that it's just ways to help you build the context for your prompt. Either pulling in premade prompts that provides certain instructions or documentation, or providing more specialized tools for the model to use along with instructions on using those tools.
They’re all bandaids
Just like C++, JavaScript and every Microsoft product in existence
All marketing names for APIs and prompts. IMO you don't need to even try to follow, because there's nothing inherently new or innovative about any of this.
It reminds me of llm output at scale. Llms tend to produce a lot of similar but slightly different ideas in a codebase, when not properly guided.
It's like JS frameworks. Just wait until a React emerges and get up to speed with that later.
That's funny. My reaction to react emerging was to run away from JS frameworks entirely.
React itself took a few years for react to decide how it should work (hooks not classes etc).
Probably same will follow with LLMs. If you find something that works for you, sorry but that will change.