Comment by elliotto
9 hours ago
I've noticed with AI people seem to want to latch onto frameworks. I think this happens because the field is changing quite quickly and it's difficult to navigate without being in it - offloading decisions to a framework is an attempt to constrain your complexity.
This occurred with langchain and now seems to be occurring with mcp. Neither of those really solved the actual problems that are difficult with deploying AI - creativity, context, manual testing, tool design etc. The owners of these frameworks are incentivized to drag people into them to attain some sort of vendor lock-in.
At my company we started building our tool based data scientist agent before MCP came out and it's working great.
MCP is something that's filled with buzzwords and seems like something created solely so that you can be "sold" something. From what I actually gathered, it's basically somehow four things rolled into one:
* A communication protocol, json-rpc esque except it can be done over stdio or via HTTP
* A discovery protocol, like Swagger, to document the "tools" that an endpoint exposes and how it should be used
* A tool calling convention, the specific sequence of tokens the LLM needs to output for something to be recognized as a tool call
* A thin glue layer orchestrating all of the above: injecting the list of available tools into the LLM context, parsing LLM output to detect tool calls and invoke them with appropriate args, and inject results back into LLM context
> * A thin glue layer orchestrating all of the above: injecting the list of available tools into the LLM context, parsing LLM output to detect tool calls and invoke them with appropriate args, and inject results back into LLM context
Yeah llm rules. You think there must be something more to it. There's not.
AI is in it's "pre react" state if you were to compare this with FE software development of 2008-2015
I think that's being generous, we haven't even had the Rails moment with AI yet. Shit, I'm not sure we've had the jQuery moment yet. I think we're still in the Perl+CGI phase.
We won’t have a rails or react for AI, that’s insane. As it gets smarter you’ll just talk to it lol.
All of this is just software engineers grasping to stay relevant
Frameworks are also a way to capture a part of the ecosystem and control it. Look at Vercel.
AI has lots of this 'fake till you make it' vibe from startups. And unfortunately it wins - because these hustler guys get a lot of money from VCs before their tools are vetted by the developers.
Yeah, and just like the web space there will be a plethora of different frameworks out there all solving the same problems in their own slightly different, uniquely crappy ways and an entire pointless industry built around ceaselessly creating and rehashing and debating this needlessly bloated ecosystem of competing solutions will emerge and employ many "ai engineers".
Outside of a few notable exceptions, the software industry has become such a joke.
>TrueState unburdens analytics teams from the repetitive analysis and accelerates the delivery of high-impact solutions.
Ehh, that's pretty vague. How does it work?
>Request demo
Oh. Well how much is it?
>Request pricing
Oh never mind
It’s like the email scams that filter people out with bad spelling and obvious red flags. If someone makes it through those hurdles they’re probably a good prospect. You weren’t really thinking of buying it, were you?
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