# AI Workspace Core Reusable operating layer for AI-assisted professional workspaces. The core is project-independent. It defines how an AI agent should maintain file-based memory, ingest communication evidence, draft recurring updates, and adjust its own commands, prompts, and skills when reusable behavior changes. --- ## Core Responsibilities - Maintain operational memory across sessions - Separate imported evidence from promoted memory - Provide reusable command and prompt patterns - Support project profiles without embedding project-specific facts in the core - Keep tooling behavior editable by the agent when the user corrects recurring output --- ## Project Profiles Each real project should provide a profile under `profiles//`. A profile declares: - project name and audience - active communication sources - ticket/work-item system - manager or stakeholder mapping - domain-specific context files - enabled commands and skills The core should never require a specific company, codebase, manager, channel name, ticket prefix, or programming stack. --- ## Memory Layers - `daily`: facts from a specific workday - `state`: current active focus and near-term constraints - `work-items`: canonical memory for active units of work - `stable-context`: durable system, domain, process, or architecture knowledge - `people`: role, stakeholder, and collaboration memory - `decisions`: confirmed decisions with ongoing impact - `tooling-behavior`: reusable rules that change commands, prompts, skills, or agent behavior See `core/memory/operational-memory.md` for the detailed rules. --- ## Integration Model Integrations extract evidence. They do not decide what becomes memory. - live communication connectors write recent evidence to `ai/inbox/` - historical archive connectors write selected evidence to `scripts//generated/` - the agent promotes only high-confidence, project-relevant facts into memory See `core/integrations/communication-model.md` for the reusable connector contract.