Paul Dix

As those tools and those models get better,

they're automatically going to be better at using InfluxDB and better at using our stuff as long as we have proper documentation in Markdown files that agents can consume, command line tooling that the agents can use.

I'm not super bullish on MCP just because at this stage, if I can have the agent use a CLI, that's what I use, but...

Yeah.

I mean, I imagine we'll be adding like more security features to the database, right?

where the security features are designed around agents accessing the database versus humans right because there's you know my guess is the if you if you take out like dashboarding basic dashboarding like i assume like agents are going to be the most frequent accessor of the database so the question is like how do you want to lock them down right you want to lock them down so they can't

mess up the data that's in there.

Maybe you want to lock down visibility in terms of what they can get to.

So, but those are all like security and access controls.

But the truth is like a lot of that stuff is the same if you have a very large enterprise organization with a bunch of humans accessing these things.

So I feel like, you know, just like I said, like for all the software development practices that mattered before just matter even more, it's the same thing.

Like

All these features matter more.

The only difference is instead of having an organization where you have 100 or 1,000 humans accessing the thing, you also have 100, 1,000, 10,000 agents accessing it and doing it much more frequently because agents can work faster than humans can.

Yeah, so we've never been a pair programming shop.

I mean, certainly like individual developers will sometimes like contact one of the other developers to like pair on something quickly, but not like, you know, agile pair programming kind of prescriptive kind of thing.

Initially, like in July of last year, we started doing like, oh, we'll have like an AI day like once a month where it's like you don't have to worry about doing any sort of like product development or stuff like that.

It's just like pick up some AI tool and do something either fun or whatever and share it with the rest of the engineering org.

We also created a Slack channel for AI stuff where it's like, okay, share your learnings with whatever tools you're using.

And recently we've started sharing skills that are getting developed inside, skills for code review or other kinds of things.