What is Shared Context?

Shared Context

Information that multiple AI agents can access simultaneously to maintain coherent collaboration. Includes project knowledge graphs, state files, configuration documents, and real-time data stores. Effective shared context prevents agents from making contradictory decisions.

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Multi-Agent Coordination Patterns: When One Agent Isn't Enough

Four practitioner-tested coordination patterns for multi-agent Claude Code workflows — fan-out, pipeline, shared-context-hub — with the vault as coordination mechanism and a decision framework for when to split.

Context Engineering Principles: The Mental Models I Use Every Day with AI Agents

Named principles for context engineering — less is more, knowledge gardening, structure over retrieval — discovered through daily agent usage, not academic theory.

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Shared Context is taught in Context Engineering for Humans — a guided sequence of 16 lessons.

After completing this path you will engineer context deliberately: recognize which context you are in and load it on purpose, externalize the assumptions and decisions that machines and colleagues silently need, structure information so it survives handoff (identifiers, atomic units, explicit relationships), and manage the switching costs that fragment thinking. Your AI sessions start warm and your writing stops being misread.

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