Comment by mupuff1234
2 days ago
I still don't understand MCP. If according to all the AI companies soon AI will replace devs than why bother with MCP?
2 days ago
I still don't understand MCP. If according to all the AI companies soon AI will replace devs than why bother with MCP?
Lock-in. LLMs are today's hammer: everything looks like a nail now. LLMs are super useful for certain tasks (generating boilerplate code, generating tests, providing examples for API usage, summarising etc.), but the demo to me just illustrates a solution in desperate search for a problem. "Create A TODO" using a chatbot? That's an example gone wrong in so many ways and goes to show what happens if you start with a solution and work your way backwards to a use case without actually thinking about it yourself...
A todo list is already a productivity tool and not an essential one. When I hear about productivity I can't help but think "but be productive doing what?"
What do we have to do that's so important we need AI, and not a chat AI but AI on steroids (supposedly)?
It's pretty much standardizing on a couple endpoints for providing a list of resources/actions/prompt templates and calling to fetch those resources/actions/templates and feed them to the model context. It's really kind of trivial, but it's nice there's a standard I guess so you can write a service that anyone can use in their favorite client.
I think that also known by another word - "documentation".
Because we're in the denial phase, doing expert systems all over again but this time on top of something that looks like NLP but isn't quite there.