STUDY MCP

“I think one thing that's becoming more clear is I think the coding agents are the kernel VGI. Everything is a coding agent. I think that's one one direction. And then, yeah, the exciting thing about that is your agent can bootstrap its own software and capabilities and actually debug and maintain them.”

“It was definitely super exciting for me because it's probably the fourth or fifth time that we rebuilt that. We've been building this since 2022. It was even right when we got access to G P G 4 in late twenty twenty two. Let's make an agent that I mean, oh, we used the word assistant at the time. There wasn't really a word agent yet.”

“We did partnerships at both Amphorpe and OpenAI at different times to try to at the time, the when we first tried, there wasn't even a constant of, like, tools yet. We designed our own, like, tool calling framework. And then we tried to fine tune the models to to use it over multiple turns. And because it didn't work well out of the box, I think yeah. The models are just too dumb and the context thing was also way too short.”

“I show that thesis to so many candidates. Like, I have it as my Chrome autofill at this point. And here's why it's not just a wrapper. I actually think more and more people understand it's not just a wrapper. And by the way, like, in the beginning, parts of what we build are wrappers on functionality that works well. But that's not really the product that that drives revenue.”

“I think there's definitely a lot of use cases where you don't want, like, a full coding agent with a compute run time. And also, you want it to be, like, more tightly permissioned. MCP inherently has a really strong permission model. Like, all you can do is call the tools. MCP is just, like, the dumb simple thing that works and it that is pretty good.”