How to Build Agent Environments and Tasks

Reliably improving agent performance requires representative benchmarks. However, creating a single task with inputs, environments, and evaluation criteria that match real-world conditions demands significant time and effort.

To address this, LangChain built a two-stage pipeline. The first stage takes execution traces, code, or human input to generate detailed specifications. The second stage automatically generates evaluation tasks and execution environments based on those specifications.

This process uses a 'World Spec' that includes project-specific information, scripts, and key definitions to manage shared knowledge. The process is iterative, and LangChain has packaged it as an eval-engineering skill so that all teams can own this workflow themselves.