it’s actually so cool to work at LangChain the…database company (??) yup, the cracked team that built SmithDB is doing a cool blog series on…

it’s actually so cool to work at LangChain the…database company (??) yup, the cracked team that built SmithDB is doing a cool blog series on “How to build the internals of a database” —> for agent scale A lot of thought goes into design decisions so that we can scale to agentic workloads that will far exceed the quantity of data anyone has needed to process in history Understanding Trace data at scale is going to be crucial to Continual Learning and broadly figuring out what our agents have been doing and it’s fun to read how db engineers solve this after prompting and looking at loss/reward graphs all day :) How do you support full-text search JSON filtering over agent traces that span up to hundreds of MBs, while keeping a median (P50) latency of 400ms? Here’s an inside look at how we built a custom inverted index from scratch for SmithDB. https://www.langchain.com/blog/full-text-se…

Source: Harrison Chase (X) | 2026-06-10