Last week LangChain announced a $20M Series A led by Sequoia and released the paid version of LangSmith, which has already been used by 1K+ teams and driven 80K signups. On this week’s episode of Unsupervised Learning, we sat down with LangChain Co-Founder and CEO Harrison Chase to talk about the current state of LLM evaluation, observability, and the agent landscape.
Last week LangChain announced a $20M Series A led by Sequoia and released the paid version of LangSmith, which has already been used by 1K+ teams and driven 80K signups. On this week’s episode of Unsupervised Learning, we sat down with LangChain Co-Founder and CEO Harrison Chase to talk about the current state of LLM evaluation, observability, and the agent landscape.
(0:00) intro
(1:07) applications of AI in the sports world
(3:26) what does LangChain do?
(7:51) building with LangSmith
(10:00) best AI eval practices
(16:51) to what extent is eval generalizable?
(21:11) the current agent landscape
(29:35) balancing present and future at LangChain
(36:27) using LangServe to deploy LangChain applications
(41:37) more complex chatbots are coming
(45:51) current AI practices that will become obsolete
(48:55) over-hyped/under-hyped
(49:25) bigger surprise in building LangChain
(51:50) how ubiquitous will open-source models be in the future?
(52:43) most exciting AI startups
(56:07) being an AI “celebrity”
(58:09) Jacob and Jordan debrief
With your co-hosts:
@jacobeffron
- Partner at Redpoint, Former PM Flatiron Health
@patrickachase
- Partner at Redpoint, Former ML Engineer LinkedIn
@ericabrescia
- Former COO Github, Founder Bitnami (acq’d by VMWare)
@jordan_segall
- Partner at Redpoint