Anthropic published a guide on August 14 detailing best practices to maximize the efficiency and value of Claude Code AI sessions. The recommendations focus on reducing token usage and managing context effectively during interactions with the Claude Code model, according to claude.com.
The guide advises users to run the `/clear` command between tasks to prevent irrelevant prior context from being sent back to the model, which helps reduce token consumption. It also suggests setting the model and effort level before starting a session, as changing these mid-conversation can increase token costs by busting the prompt cache. Additionally, users are encouraged to @-mention files instead of naming them, which attaches files directly to messages and saves read calls or searches. Lastly, adding quiet flags to noisy commands or running them in a subagent prevents command output from cluttering the conversation.
These practices address common inefficiencies in AI session management, helping users optimize their interactions with Claude Code. By controlling context and token usage, users can reduce costs and improve response relevance. This is particularly important as AI models like Claude Code gain traction in enterprise applications where cost and efficiency are critical. The guide complements Anthropic’s broader efforts to enhance user experience and operational efficiency in AI deployments.
The blog post, authored by Lydia Hallie and published on claude.com, serves as a practical resource for existing and prospective Claude Code users aiming to optimize their AI workflows.