Results for “context-layer”

Optimizes agent context setup by structuring rules, specs, source files, error output, and conversation history to improve output quality.

Provides structured guidance for building production-grade AI agent systems through context engineering, covering fundamentals, architectural patterns, operational excellence, and evaluation.

Install and configure Acontext, a memory layer for AI agents that provides persistent sessions, file storage, and skill management.

Progressively refines context retrieval in multi-agent workflows to solve the subagent context problem.