The best AI agents need less code than you think
From the video description
Ben Tannyhill is a product manager at LangChain, where he's building LangSmith Engine—an agent that finds and fixes your agent's failures. Engine continuously analyzes your production traces, clusters them into actionable issues, and opens pull requests to fix them. Engine's architecture is a lot like an org chart: a main model delegating to a team of cheaper, faster sub-agents. It launched in public beta at Interrupt 2026, and in this conversation, Ben unpacks why it uses a sandbox as a tool, how the team turned it into a self-improving agent that learns from its own traces, and the hard problem of testing a fix before it ships.
Topics
Sources
Video by LangChain, played through YouTube.
- Indie Picks
Data and selection notes
Indie Picks uses video metadata for classification. The description above is an uploader excerpt, not an independent review.
Indie Picks: Independently collected SaaS and AI product videos, organized by a founder handbook. Topics and relevance are metadata-indexed; full-video editorial review has not been completed. Descriptions are uploader excerpts where available.
Views, duration and playback status refresh separately from the published catalog. When an update fails, existing data remains visible.
Selection checks
- SaaS & AI candidates: Matches the configured criteria
- Editor-approved picks: Editorial review is required