Your coding agent bill doubled. Here’s how to fix it.

LangSmith addresses the challenges faced by teams using multiple coding agents, such as the increased costs and fragmented data visibility that result from "tokenmaxxing," where excessive spending is mistakenly equated with productivity. The solution involves consolidating data from various agents like Claude Code, Codex, Cursor, and GitHub Copilot Chat into a unified trace model, enabling teams to see and compare expenses across tools in a consistent format. This visibility allows for optimization, where inefficiencies are identified and actionable recommendations are provided by the Engine feature to refine workflows. Additionally, the LLM Gateway offers governance by capping costs at user, team, and organizational levels, and it can integrate open-source models for cost-effective alternatives in appropriate scenarios. By providing a single platform for monitoring, debugging, and measuring coding sessions, LangSmith empowers teams to manage their AI tool usage effectively, ensuring that spending aligns with actual value delivered.

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