commit e9df1a1efe2c0388f8f61e8483b4618a637a78b9 Author: saravanakumardb1 Date: Tue Mar 10 07:23:30 2026 -0700 docs(prd): update requirements diff --git a/docs/PRD.md b/docs/PRD.md new file mode 100644 index 0000000..6899f38 --- /dev/null +++ b/docs/PRD.md @@ -0,0 +1,58 @@ +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 │ ││ └──────────┘ └──────────┘ └──────────┘ └──────────────────┘ ││ ┌──────────┐ ┌─────── \ No newline at end of file