Try out LangSmith Fine-Tuning today with our dedicated CLI smithtune A huge part of post training is finding and processing the right data. Our CLI handles pulling, selecting, processing trajectories from LangSmith, training on @FireworksAI_HQ and @baseten, then evaling with LangSmith. Let me know what you think!

Trajectories make it easier than ever to analyze long agent runs. They are now a first-class citizen within LangSmith. We also spent a lot of time ensuring our trajectory format handles things like deferred tool calling and context compaction well.

We’re looking for someone to lead SmithDB at LangChain! SmithDB is the database we’ve built from the ground up to power LangSmith. It’s optimized specifically for the access patterns that emerge when you’re storing and querying enormous volumes of agent traces. It’s serving production traffic at significant scale with great performance, but it’s still early. The problems we are solving are genuinely fun and very hard: indexing, query execution, compaction, ingestion specifically for agent observability + making all of this fast and cost-efficient at massive scale. We’re looking for an exceptional engineering leader to take ownership of this critical project. You’re likely a great fit if you’ve built database or distributed systems, led strong engineering teams through technically demanding projects, and have exceptional execution and project management skills. Apply here or DM me directly: Learn more about SmithDB here: