James Reggio

speaker

667 appearances 1 recordings 1 series first heard Jan 2026 last heard 17 Jan

James Reggio’s voice in public audio — every appearance, attributed to the second.

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Latent Space: The AI Engineer Podcast · Brex’s AI Hail Mary — With CTO James Reggio · 17 Jan 2026 podcast

I think January 2023, that would have been, uh, was try to put together some internal infrastructure that made it possible for us to deploy, pro deploy, manage, version in Eval prompts, uh, and then be able to manage uh like data egress and model routing and uh have some very basic like observability and cost monitoring uh in an LM gateway.

So that's that's infrastructure that we stood up and it still continues to power a lot of those smaller

uh more let's say like precise applications of LLM.

So like for instance, we've uh we set up a completely automated uh pipeline for um evaluating uh customer applications to get them onboarded instantly to BREX, which is something that used to require um human intervention either for underwriting or KYC.

But now we basically have a series of of agents and um and particularly like research agents

So we'll go and do the work that humans would normally do.

And so that's running on top of this uh this hand rolled uh framework.

And then for the agent sum Brex that we announced in our fall release, which is like this agentic layer that we're building that sort of sits on top of BREX and can embody workflows that a finance team would normally uh hire humans for.

We've actually uh started using Mastra for that as like the kind of primary

Primary framework for for accelerating us.

We actually have built everything in TypeScript, um, uh which is another like technology choice that's uh that answers the question of like what will we do if we started Brex today, but isn't the case for all of our existing backend code, which is either Kotlin or Elixir.

And then we have uh we have a mix of PG vector, PineCone, and uh like I think what we've seen is

We're always we're always reevaluating the tech and framework choices as we go, uh, because the half life of code has declined so significantly with agenda coding, it's actually quite uh easy for us and for anyone else to to kind of try on for size a variety of different pieces of tech to to figure out what is going to be most economic for solving the problem.

Double click on

Yeah.

I mean I think that the main the main reason that w we adopted Mastro is that it provided the ergonomics that we were actually uh that w the ergonomics of Mastro are quite similar to the internal um LLM framework that we built two and a half years ago.

Uh whereas like Langchain was available at the time two and a half, three years ago.

Uh it didn't quite feel uh right to us when we were trying to

Um it kind of addressed the things that weren't the the pieces that we we needed to address, which was like being able to have really simple um absorbability and and uh logging tracing.

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