docs(prd): update requirements

docs/PRD.md

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+Product Requirements Document: AI-Agent-First Knowledge Platform
+
+Version: 1.0
+Date: March 10, 2026
+Author: Product Team
+Status: Draft
+1. Executive Summary
+
+This platform is being built from the ground up as an AI-agent-first knowledge platform — a system where AI agents are first-class citizens alongside human users. Every note, workspace, workflow, and API is designed to be created, consumed, and orchestrated by both humans and autonomous agents.
+
+The current application is a capable note-taking app with workspaces, hashtags, posts, and bolted-on AI features. The rebuild inverts the paradigm: instead of a human app with AI helpers, it becomes a knowledge operating system where agents think, collaborate, and act — and humans supervise, guide, and participate.
+Vision Statement
+
+    "The knowledge layer for the agentic era — where humans and AI agents create, organize, reason over, and act on knowledge together."
+
+Key Differentiators
+
+    Agent-native data model — Every entity (note, task, artifact) is structured for machine readability while remaining human-friendly
+    MCP-native architecture — Full Model Context Protocol support as the primary integration surface
+    Knowledge graph, not folders — Semantic relationships replace hierarchical organization
+    Event-driven agent orchestration — Agents react to knowledge changes in real-time
+    Multi-tenant agent identity — Agents have identities, permissions, audit trails, and reputation just like human users
+
+2. Problem Statement
+Current Limitations
+Problem	Impact
+Notes are unstructured blobs of text	Agents can't reliably parse, query, or reason over content
+AI is an afterthought (chat sidebar)	No deep integration; agents can't autonomously create or manage knowledge
+No agent identity system	Can't track what an agent did, why, or with what authority
+API is human-UI-coupled	No clean programmatic interface for agent tooling
+Flat organization (workspaces + hashtags)	No semantic relationships, no knowledge graph
+Single-user mental model	No agent-to-agent collaboration or delegation
+Hardcoded AI endpoints	Can't swap models, providers, or agent frameworks
+Backend split across multiple services	Fragile, hard to extend, inconsistent APIs
+No event/webhook system	Agents can't react to changes or trigger workflows
+Block-based billing is vague	No clear unit economics for agent compute
+Market Opportunity
+
+The AI agent ecosystem is exploding — every major LLM provider ships agent frameworks (OpenAI Agents SDK, Anthropic MCP, Google A2A, LangChain, CrewAI, AutoGen). But agents lack a persistent, shared knowledge layer that isn't just a vector database. This platform fills that gap: a place where agents store their work, share context, collaborate with humans, and build institutional knowledge.
+3. Target Users
+3.1 Human Users
+Persona	Description	Key Needs
+Knowledge Worker	Individual using notes, tasks, research	Fast capture, AI-assisted organization, search
+Team Lead	Manages a team with shared workspaces	Oversight of agent work, approval workflows, analytics
+Developer	Builds agent workflows, integrations	Clean APIs, MCP tools, webhooks, SDK
+Creator	Publishes posts, builds content	AI-assisted writing, scheduling, distribution
+3.2 AI Agent Users
+Persona	Description	Key Needs
+Research Agent	Gathers, synthesizes, and stores information	Read/write notes, semantic search, source linking
+Workflow Agent	Orchestrates multi-step processes	Task management, status updates, human-in-the-loop
+Analysis Agent	Processes data and produces insights	Structured output storage, chart/artifact creation
+Assistant Agent	Responds to user queries using knowledge base	Full-text + semantic search, context retrieval
+Integration Agent	Syncs data between external systems and the platform	Webhooks, CRUD APIs, bulk operations
+Monitoring Agent	Watches for changes and triggers actions	Event subscriptions, real-time notifications
+4. Architecture Overview
+4.1 High-Level Architecture
+
+┌─────────────────────────────────────────────────────────────────┐│                        CLIENT LAYER                             ││                                                                 ││   ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────────┐  ││   │  Web UI  │  │Mobile PWA│  │   CLI    │  │  Agent SDKs  │  ││   │ (React)  │  │  (React) │  │(Terminal)│  │ (TS/Py/Rust) │  ││   └────┬─────┘  └────┬─────┘  └────┬─────┘  └──────┬───────┘  ││        └──────────────┴─────────────┴───────────────┘          │└────────────────────────────┬────────────────────────────────────┘                             │┌────────────────────────────┼────────────────────────────────────┐│                     API GATEWAY LAYER                           ││                                                                 ││   ┌────────────────────────┴────────────────────────────────┐  ││   │              Unified REST + GraphQL API                  │  ││   │         (Auth, Rate Limiting, Agent Identity)            │  ││   └────────────────────────┬────────────────────────────────┘  ││                            │                                    ││   ┌────────────┐  ┌───────┴───────┐  ┌──────────────────┐     ││   │  MCP Server│  │  WebSocket    │  │  Webhook Engine  │     ││   │  (Tools)   │  │  (Real-time)  │  │  (Outbound)      │     ││   └────────────┘  └───────────────┘  └──────────────────┘     │└────────────────────────────┬────────────────────────────────────┘                             │┌────────────────────────────┼────────────────────────────────────┐│                      SERVICE LAYER                              ││                                                                 ││  ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────────────┐  ││  │Knowledge │ │ Agent    │ │Workflow  │ │   AI Inference   │  ││  │ Service  │ │ Service  │ │ Engine   │ │   Gateway        │  ││  └──────────┘ └──────────┘ └──────────┘ └──────────────────┘  ││  ┌──────────┐ ┌───────