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ainative

Companion software for the AI Native Business book by Manav Sehgal — a local-first agent runtime and builder scaffold for AI-native businesses.

AI Business Operating System npm Next.js 16 React 19 TypeScript Claude Agent SDK OpenAI Codex App Server License

ainative.business · GitHub

Quick Start

npx ainative-business

Open localhost:3000. That's it — zero config, local SQLite, own your data.

Profiles & Policies · Blueprints & Schedules · Built-in Playbook · Open Source

ainative home workspace

Home Workspace Reusable Profiles Workflow Blueprints Governed Execution
Workspace briefing with active work, pending review, project signals, and live activity Specialist definitions with prompts, tool policy, and runtime tuning you can reuse Pre-configured templates with dynamic forms, YAML editing, and lineage tracking Human-in-the-loop approvals, tool permissions, and ambient supervision

ainative home workspace below fold — projects, activity feed, and signals


Why ainative

The AI agent stack is broken for business operators. You can spin up an agent in minutes — but running it reliably for real work means stitching together orchestration, governance, cost controls, and team coordination yourself. ainative closes that gap with a single local-first platform where agents do the work and you stay in control.

  • Local-first — SQLite database, no cloud dependency, npx ainative-business and go
  • Multi-provider — Claude Code + OpenAI Codex App Server behind one runtime registry
  • Your rules, enforced — Tool permissions, inbox approvals, and audit trails for every agent action
  • Your AI team — 21 specialist profiles ready to deploy, each with instructions, tool policies, and runtime tuning
  • Business processes, automated — 6 workflow patterns (sequence, planner-executor, checkpoint, parallel, loop, swarm)
  • Know what you spend — Usage metering, budgets, and spend visibility per provider and model

About Author

Manav Sehgal

Solutions Leader, AWS Frontier AI.

Author, AI Native open book. 2M+ Kaggle views. Ex Amazon AGI.

A personal research project

ainative & AI Native — Free and open source. Building AI Native over weekends, using personal laptop and capped AI plans.

Executive Credentials

  • Harvard — Disruptive Strategy
  • MIT Sloan — Design Thinking
  • Berkeley Haas — Leading Innovative Change

Short version

"ainative is a personal research project exploring what it takes to build AI-native on a shoestring budget over weekends." The AI Native open book serves as its 14-chapter playbook expanding this research.

Bio

Manav is a solutions leader at AWS Frontier AI, collaborating with Anthropic, NVIDIA, and Disney on production AI and agentic systems. His 25-year career spans Xerox PARC (1996), HCL's digital practice, Daily Mail, Amazon AGI, and AWS, where he has delivered scale AI programs for Amazon Retail and Alexa. He led AWS pandemic response which was honored by President of India award for the customer. He holds credentials from Harvard, MIT Sloan, Berkeley Haas. He has studied Computer Engineering and Lean Management.

Research Premise

"ainative is a personal research project exploring what an AI-native operating system looks like." The AI Native book is its 14-chapter playbook for building autonomous business systems with AI agents.

Attribution

ainative and AI Native are personal works of Manav Sehgal created in own personal time and resources. While they may refer to AWS technologies which enable the AI Native promise, the opinions expressed in the website are author's personal opinions and not that of the employer.

Previously published

  • Data Science Solutions (2017)
  • React Speed Coding (2015)

Runtime Bridge

Run the same business process on different AI providers without changing a line of configuration. ainative's shared runtime registry routes tasks, schedules, and workflow steps through Claude Code (Anthropic Claude Agent SDK) and OpenAI Codex App Server, landing everything in the same inbox, monitoring, and cost surfaces. Switching providers is a settings change, not a rewrite.


Feature Highlights

Feature What it does
🏠 Home Workspace Workspace briefing with active work, pending review, project signals, and live activity
📌 Task Execution Status-driven execution board for planned, queued, running, completed, and failed work
📁 Projects Portfolio-level organization with scoped context and working directories
🔀 Workflows Multi-step orchestration with sequence, planner-executor, and checkpoint patterns
🧩 Workflow Blueprints Reusable templates for spinning up common automations quickly
🧠 Agent Profiles Reusable specialist definitions with prompts, tool policy, and runtime tuning
Schedules Recurring and one-shot automations with cadence, expiry, and firing controls
📄 Documents Upload, preprocess, inspect, and link files to tasks and projects
📊 Tables Airtable-like structured data with spreadsheet editing, charts, triggers, and agent tools
📥 Human-in-the-Loop Inbox Approve tool use, answer questions, and review results from one queue
💬 Chat Tool catalog with model selection, @ mentions, slash commands, and browser automation
👀 Monitoring Live runtime visibility with log streaming, filters, and health signals
🔁 Provider Runtimes Shared runtime layer with Claude Code and OpenAI Codex App Server adapters
🧪 Parallel + Swarm Workflows Bounded fork/join and swarm orchestration without a free-form graph editor
💸 Cost & Usage Provider-aware metering, budgets, and spend visibility for governed runs
🚨 Ambient Approvals Shell-level approval prompts that keep Inbox as the durable supervision queue
🔒 Tool Permissions Trusted-tool policies with explicit "Always Allow" rules
📋 Kanban Board Inline editing, bulk operations, and persistent board state
🤖 AI Assist → Workflows Bridge task assist recommendations into governed workflow execution
🧬 Agent Self-Improvement Agents learn patterns from execution history with human-approved context evolution
🎯 Tool Permission Presets Pre-configured permission bundles (read-only, git-safe, full-auto) with layered apply/remove
📦 Workflow Context Batching Workflow-scoped proposal buffering with batch approve/reject for learned context
🧪 E2E Test Automation API-level end-to-end test suite covering both runtimes, 4 profiles, and 4 workflow patterns
⌨️ Command Palette Global ⌘K search for fast navigation across tasks, projects, workflows, and settings
🧱 Skill Composition Activate up to 3 skills at once with conflict detection and runtime-aware capability gates
🔎 Filters & Saved Searches #key:value filter grammar, pinned and saved searches surfaced in ⌘K palette
🛡️ Upgrade Detection Hourly upstream check with in-app notifications and guided merge sessions
📖 Playbook Built-in documentation with usage-stage awareness, adoption heatmap, and guided learning journeys
📚 Living Book AI-native book reader with 9 chapters, agent-powered regeneration, staleness detection, and reading paths
🌐 Environment Control plane for Claude Code and Codex CLI environments with scanning, caching, sync, and templates
🔧 Browser Tools Chrome DevTools and Playwright MCP integration for browser automation in chat and task execution

Architecture

ainative architecture diagram

Key design decisions:

  • Server Components for reads — Pages query SQLite directly, no API layer for reads
  • Fire-and-forget executionPOST /api/tasks/{id}/execute returns 202, agent runs async
  • Notification-as-queue — The notifications table is the message bus for human-in-the-loop; agents poll it via canUseTool
  • SSE for streaming/api/logs/stream pushes agent logs to the browser in real time
  • Provider runtime abstraction — Tasks, schedules, workflows, task assist, and health checks route through shared runtime adapters instead of provider-specific entry points
  • Reusable agent profiles — Profiles define instructions, allowed tools, runtime tuning, and MCP configs for repeated use
  • Permission pre-check — Saved "Always Allow" patterns bypass the notification loop for trusted tools
  • Learned context loop — Pattern extraction → human approval → versioned context injection creates a supervised self-improvement cycle
  • Permission presets — Layered preset bundles (read-only ⊂ git-safe ⊂ full-auto) that compose with individual "Always Allow" patterns

Feature Deep Dives

Core

Home Workspace

Workspace-level briefing with active work, pending review, failed items, project counts, and live agent activity. The home view is designed for daily triage before you drill into execution, inbox, or monitoring detail.

Task Execution

Status-driven execution board with five columns: Planned → Queued → Running → Completed → Failed. Filter across projects, create tasks inline, and open task detail to inspect status, description, and runtime state without leaving the board.

ainative kanban board

Table View
Dashboard table view

Projects

Create and organize projects as containers for related tasks. Each project can specify a working directory — agent tasks resolve cwd from the project's path, enabling agents to operate on external codebases. Server-rendered project cards with task counts, status badges, and a detail view at /projects/[id].

Project Cards Project Detail
Project cards overview Project detail view

Agent

Provider Runtimes

ainative supports two governed execution runtimes behind a shared runtime registry:

  • Claude Code via the Anthropic Claude Agent SDK
  • OpenAI Codex App Server via codex app-server

Tasks, schedules, and workflow steps can target a runtime explicitly, while settings exposes runtime-specific authentication and health checks. Runtime-specific execution still lands in the same inbox, monitoring, and task state surfaces.

Agent Integration

Claude Agent SDK integration with the canUseTool polling pattern remains the default Claude execution path. Tasks are dispatched fire-and-forget and run asynchronously, while every tool call, reasoning step, and decision is surfaced through inbox approvals and monitor logs.

OpenAI Codex Runtime

OpenAI Codex App Server is integrated as ainative's second governed runtime. Codex-backed tasks preserve project working directories, document context, resumable thread IDs, inbox approval requests, user questions, and provider-labeled logs. The same runtime can also power task assist, scheduled firings, and workflow child tasks.

Agent Profiles

Profile-backed execution with specialist definitions for different job types. Each profile packages instructions, allowed tools, max turns, and output format so teams can reuse behavior intentionally instead of relying on ad hoc prompts. Profile cards display role-based icon circles with keyword-inferred colors (blue for work, purple for personal), alongside domain tags, runtime badges, and tool counts. Workflow steps and schedules can reference profiles directly, and runtimes can be selected independently when provider support differs.

ainative agent profiles with role-based icon circles

Workflows

Multi-step task orchestration with six patterns:

  • Sequence — Steps execute in order
  • Planner→Executor — One agent plans, another executes each step
  • Human-in-the-Loop Checkpoint — Pauses for human approval between steps
  • Parallel — Concurrent branch execution with fork/join synthesis
  • Loop — Iterative agent execution with configurable stop conditions
  • Swarm — Mayor/workers/refinery multi-agent orchestration

State machine engine with step-level retry, project association, and real-time status visualization.

Parallel + Swarm Workflows

ainative supports two bounded expansion patterns on top of the workflow engine:

  • Parallel research fork/join — 2-5 concurrent branches followed by one synthesis step
  • Swarm orchestration — mayor → worker pool → refinery with retryable stages and configurable worker concurrency

Both patterns preserve the same governed task model, runtime selection, monitoring stream, and workflow detail surface instead of introducing a separate orchestration product.

AI Task Assist

AI-powered task creation: generate improved descriptions, break tasks into sub-tasks, recommend workflow patterns, and estimate complexity through the shared runtime task-assist layer. Claude and OpenAI task assist now both route through the provider runtime abstraction.

AI Assist → Workflow Creation

Bridge from AI task assist to workflow engine: when task assist recommends a multi-step plan, a "Create as Workflow" button converts the recommendation into a validated workflow definition with per-step profile assignments, dependency ordering, and pattern selection across all six workflow types. The WorkflowConfirmationSheet lets operators review and edit steps, profiles, and configuration before creating the workflow. A keyword-based profile suggestion fallback ensures steps get reasonable profile assignments even without the AI classifier.

Agent Self-Improvement

Agents learn from execution history through a human-approved instruction evolution loop. After each task completion, the pattern extractor analyzes logs and proposes context updates — concise behavioral rules the agent should follow in future runs. Operators approve, reject, or edit proposals before they take effect. Learned context is versioned with rollback support and size-limited summarization to prevent unbounded growth. A sweep agent can audit the codebase for improvement opportunities and create prioritized tasks from its findings.

Workflow Context Batching

During workflow execution, the pattern extractor buffers context proposals into a learning session instead of creating individual notifications per proposal. When the workflow completes, all proposals are surfaced as a single batch for review. Operators can approve all, reject all, or review individually — reducing notification noise from multi-step workflows while preserving human oversight. The batch review component integrates into the existing pending approval host.

Session Management

Resume failed or cancelled agent tasks with one click. Tracks retry counts (limit: 3), detects expired sessions, and provides atomic claim to prevent duplicate runs.

Autonomous Loop Execution

Iterative agent loop pattern with four stop conditions: max iterations, time budget, human cancel, and agent-signaled completion. Each iteration creates a child task with previous output as context. Loop status view with iteration timeline, progress bar, and expandable results. Pause/resume via DB status polling.

Agent Profile Catalog

Curated agent profiles across work and personal domains, built as portable Claude Code skill directories with profile.yaml sidecars. The profile gallery displays role-based icon circles with keyword-inferred colors and supports domain filtering and search, while YAML customization, GitHub import, and behavioral smoke tests keep profile behavior inspectable and reusable.

Workflow Blueprints

Pre-configured workflow templates across work and personal domains. Browse blueprints in a gallery with pattern-colored icon circles, domain tags, and difficulty badges. Preview steps and required variables, fill in a dynamic form, and create draft workflows with resolved prompts and profile assignments. Create custom blueprints via YAML or import from GitHub URLs. Lineage tracking connects workflows back to their source blueprint.

ainative workflows with keyword-inferred icon circles

Workflow Detail
Workflow detail with steps and status

Documents

Document Management

Full document browser at /documents with table and grid views. Upload files with drag-and-drop, preview images/PDFs/markdown/code inline, search by filename and extracted text, and filter by processing status or project. Bulk delete, link/unlink to projects and tasks.

Table View Grid View
Documents table view Documents grid view

Document Preprocessing

Automatic text extraction on upload for five file types: text, PDF (pdf-parse), images (image-size), Office documents (mammoth/jszip), and spreadsheets (xlsx). Extracted text, processed paths, and processing errors are tracked per document.

Agent Document Context

Documents linked to a task are automatically injected into the agent's prompt as context. The context builder aggregates extracted text from all linked documents, giving agents access to uploaded reference material without manual copy-paste.

Tables

Airtable-like structured data system at /tables with 14 features. Create tables from scratch, import from CSV/XLSX documents, or use one of 12 built-in templates across 5 categories. Each table includes an inline spreadsheet editor with keyboard navigation, type-aware cell renderers, computed columns with formula support (12 functions including sum, avg, if, daysBetween), and optimistic saves.

Table List Spreadsheet Editor
Tables list view Table spreadsheet editor
Charts Template Gallery
Table charts tab Table template gallery
  • Charts — Bar, line, pie, and scatter charts with configurable X/Y axes and aggregation
  • Workflow triggers — Automated actions fired when row data matches conditions
  • 12 agent tools — Agents can list, query, aggregate, search, add/update/delete rows, and create tables
  • Cross-table relations — Link rows across tables with searchable relation combobox
  • Export — CSV, XLSX, and JSON export for any table
  • Row versioning — History tab with snapshot-before-mutation and rollback to previous versions

Knowledge

Playbook

Built-in documentation system at /playbook with usage-stage awareness that adapts content to your experience level (new, early, active, power user). Browse feature reference docs and guided learning journeys organized by persona (Personal, Work, Power User, Developer). Adoption heatmap tracks which features you've explored, while journey cards show progress through multi-step learning paths. Markdown rendering with automatic internal link resolution, table of contents, related docs, and screengrab embedding.

ainative playbook documentation

Living Book

AI-native book reader at /book with 9 chapters across 3 parts (Foundation, Intelligence, Autonomy). Each chapter is generated from ainative's own source code and feature docs by the document-writer agent — making this a book that writes itself.

  • Chapter regeneration — one-click regeneration via the document-writer agent profile with fire-and-forget task execution
  • Staleness detection — git-based change tracking compares source file timestamps against lastGeneratedBy frontmatter to show when chapters need updating
  • Live progress streaming — SSE subscription shows real-time agent steps during generation (Reading files → Planning → Composing → Writing) with fade-in animation
  • Reading paths — 4 persona-based paths (Getting Started, Team Lead, Power User, Developer) filter chapter navigation
  • Try It Now — each chapter links to related Playbook feature docs and user journeys
  • Author's Notes — collapsible callout blocks with behind-the-scenes commentary

Environment

Environment

ainative doubles as a control plane for AI coding environments — scanning, caching, and syncing configuration for Claude Code and Codex CLI across projects. The environment dashboard surfaces detected tools, active configurations, git checkpoint status, and health scores.

  • Environment Scanner — detects Claude Code and Codex CLI configurations, MCP servers, skills, and project settings
  • Environment Cache — persists scanned state for fast dashboard rendering without re-scanning
  • Environment Dashboard — unified view of all detected environments with health indicators
  • Git Checkpoint Manager — tracks environment state via git commits for rollback and comparison
  • Environment Sync Engine — bidirectional sync between local config and cached state
  • Project Onboarding — guided flow for setting up new projects with environment-aware defaults
  • Environment Templates — reusable environment configurations for common project types
  • Cross-Project Comparison — compare environment settings across projects
  • Skill Portfolio — aggregate view of skills across all detected environments
  • Environment Health Scoring — composite health score based on configuration completeness and freshness
  • Agent Profile from Environment — auto-generate agent profiles from detected environment capabilities

ainative environment dashboard

Browser Tools

Enable browser automation in chat and task execution through two MCP integrations: Chrome DevTools MCP (29 tools for connecting to a running Chrome instance via CDP) and Playwright MCP (50+ tools for headless browser automation). Configure both from Settings with independent toggles and permission tiering — read-only operations auto-approve while mutations are gated through the inbox approval flow.

Platform

Tool Permission Persistence

"Always Allow" option for agent tool permissions. When you approve a tool, you can save it as a pattern (e.g., Bash(command:git *), Read, mcp__server__tool). Saved patterns are checked before creating notifications — trusted tools are auto-approved instantly. Manage patterns from the Settings page. AskUserQuestion always requires human input.

Ambient Approvals

Pending permission requests now surface through a shell-level approval presenter on any route, so operators can respond without leaving the page they are working on. Inbox remains the durable queue and source of truth, while the ambient surface provides the fast path for active supervision.

Tool Permission Presets

Pre-configured permission bundles that reduce friction for common tool approval patterns. Three layered presets — read-only (file reads, glob, grep), git-safe (adds git operations), and full-auto (adds write, edit, bash) — compose with existing "Always Allow" patterns. Presets are layered: enabling git-safe automatically includes read-only patterns; removing git-safe only strips its unique additions. Risk badges indicate the trust level of each preset. Manage presets from the Settings page alongside individual tool permissions.

Upgrade Detection

Hourly poller checks the upstream origin/main for new commits and surfaces them via an in-app UpgradeBadge + notification queue. If three consecutive checks fail, a single deduplicated "Upgrade check failing" notification is inserted (and cleared on the next successful tick). The upgrade-assistant profile drives guided merge sessions end-to-end — including free-form questions and 3-choice option cards when a merge conflict or drifted main requires operator input. Dev repos are fully gated via STAGENT_DEV_MODE and a .git/ainative-dev-mode sentinel so contributor pushes are never blocked.

Schedules

Time-based scheduling for agent tasks with human-friendly intervals (5m, 2h, 1d) and raw 5-field cron expressions. One-shot and recurring modes with pause/resume lifecycle, expiry limits, and max firings. Each firing creates a child task through the shared execution pipeline, and schedules can now target a runtime explicitly. Scheduler runs as a poll-based engine started via Next.js instrumentation hook.

ainative schedules

Micro-Visualizations

Pure SVG chart primitives (Sparkline, MiniBar, DonutRing) with zero charting dependencies. Integrated into: homepage stats cards (7-day trends), activity feed (24h bar chart), project cards (completion donuts), monitor overview (success rate), and project detail (stacked status + 14-day sparkline). Full accessibility with role="img" and aria-label.

Cost & Usage

Provider-normalized metering tracks token and spend activity across tasks, resumes, workflow child tasks, schedules, task assist, and profile tests. The dedicated Cost & Usage surface adds summary cards, trend views, provider/model breakdowns, and budget-aware audit visibility on top of the usage ledger.

ainative cost and usage dashboard

UI & DevEx

Inbox & Human-in-the-Loop

When an agent needs approval or input, a notification appears in your inbox. Review tool permission requests with "Allow Once" / "Always Allow" / "Deny" buttons, answer agent questions, and see task completion summaries. Supports bulk dismiss and 10s polling.

ainative inbox approval flow

Expanded Notification
Inbox notification expanded

Chat

Conversational control plane for all workspace primitives — projects, tasks, workflows, documents, and profiles are all reachable from the chat surface. The chat interface is organized as a tool catalog with five categories (Explore, Create, Debug, Automate, Smart Picks) that help discover workspace capabilities. Progressive 5-tier context injection (~53K token budget) builds workspace awareness from lightweight summaries up to full document content. @ mentions let you reference documents and entities directly in prompts with fuzzy search autocomplete, injecting their content as context. Slash commands (/) provide quick access to tools and actions. Multi-provider model selection with cost tiers ($, $$, $$$) spans Claude Haiku through Opus and GPT-5.x models. Browser automation via Chrome DevTools and Playwright MCP enables screenshot capture and web interaction from chat. Quick Access navigation pills in responses provide entity deep-linking. ainative CRUD tools let you create, update, and delete workspace entities through natural language.

ainative chat conversation with @ document context

Tool Catalog Model Selector Create Tab
Chat tool catalog with category tabs Chat model selector with cost tiers Chat Create category prompts

Skill Composition

Activate up to three skills in a single conversation with conflict detection and runtime-aware capability gates. The Skills tab in the chat popover surfaces + Add buttons on inactive skills, active badges with deactivate actions, and an "N of M active" indicator. When two skills issue polarity-divergent directives on shared keywords, a conflict dialog previews the excerpts and lets you confirm with force:true or back out. Composition honors the runtime capability matrix — Claude Code and Codex App Server support up to 3 active skills, while Ollama stays at 1. Conversations persist active skills through an additive active_skill_ids column that preserves legacy single-skill reads.

Filters & Saved Searches

Structured #key:value filter grammar across chat, documents, and the ⌘K palette. The shared FilterInput parser accepts bare clauses, quoted values (#tag:"needs review"), and free text — clauses AND with surface-specific Select filters and sync to URL params for shareable, refresh-persistent views. Save any filter expression with a rename footer; saved searches appear as a dedicated group in the mention popover and in the command palette, so views built in one surface are reachable from anywhere. Pinned saved searches sit at the top of both lists for zero-click recall.

Monitoring

Real-time agent log streaming via Server-Sent Events. Filter by task or event type, click entries to jump to task details, and auto-pause polling when the tab is hidden (Page Visibility API).

ainative monitoring dashboard

Content Handling

File upload with drag-and-drop in task creation. Type-aware content preview for text, markdown (via react-markdown), code, and JSON. Copy-to-clipboard and download-as-file for task outputs.

Settings

Configuration hub with provider-aware sections: Claude authentication (API key or OAuth), OpenAI Codex runtime API-key management, chat defaults (model selection), browser tools (Chrome DevTools and Playwright MCP toggles), runtime configuration (SDK timeout and max turns), tool permissions (saved "Always Allow" patterns with revoke), permission presets, budget guardrails, database snapshots (automatic backups with configurable retention and one-click restore), and data management.

ainative settings

Browser Tools Permission Presets Budget Configuration
Browser tools MCP toggles Tool permission presets Budget configuration

CLI

The npx ainative entry point boots a Next.js server from the published npm package. It is built from bin/cli.ts into dist/cli.js using tsup, and serves as the primary distribution channel — no clone required.

Database

SQLite with WAL mode via better-sqlite3 + Drizzle ORM. 27+ tables including core tables: projects, tasks, workflows, agent_logs, notifications, documents, schedules, settings, learned_context, usage_ledger, conversations, chat_messages, environments, environment_configs. Self-healing bootstrap — tables are created on startup if missing.

Command Palette

Global ⌘K command palette for fast navigation and search across tasks, projects, workflows, and settings. Recent items, fuzzy search, and keyboard-driven navigation.

Empty Palette Search Results
Command palette empty state Command palette search results

App Shell

Responsive sidebar with collapsible icon-only mode, custom ainative logo, tooltip navigation, dark/light/system theme, and OKLCH hue 250 blue-indigo color palette. Built on shadcn/ui (New York style) with PWA manifest and app icons. Routes: Home, Dashboard, Inbox, Chat, Projects, Workflows, Documents, Monitor, Profiles, Schedules, Cost & Usage, AI Native Book, User Guide, Environment, Settings.

E2E Test Automation

API-level end-to-end test suite built on Vitest with 120-second timeouts and sequential execution. Five test files cover single-task execution, sequence workflows, parallel workflows, blueprints, and cross-runtime scenarios across both Claude and Codex backends. Tests skip gracefully when runtimes are not configured, preventing CI failures. Run with npm run test:e2e.


Tech Stack

Layer Technology Why
Framework Next.js 16 + React 19 Server Components for zero-API reads, Turbopack for fast dev
Language TypeScript (strict) End-to-end type safety from DB schema to UI
Styling Tailwind CSS v4 + shadcn/ui Utility-first CSS with accessible component primitives
Database SQLite (WAL) + Drizzle ORM Zero-config embedded DB, type-safe queries, concurrent reads
AI Runtime @anthropic-ai/claude-agent-sdk + codex app-server Governed Claude and OpenAI execution behind a shared runtime layer
CLI Commander + tsup Familiar CLI framework, fast ESM bundling
Testing Vitest + Testing Library Fast test runner with React component testing
Content react-markdown + remark-gfm Full GitHub-flavored markdown rendering
Validation Zod v4 Runtime type validation at system boundaries
Documents pdf-parse, mammoth, xlsx, image-size Multi-format document preprocessing
Scheduling cron-parser Cron expression parsing and next-fire-time computation

Development

npm run dev            # Next.js dev server (Turbopack)
npm run build:cli      # Build CLI → dist/cli.js
npm test               # Run Vitest
npm run test:coverage  # Coverage report
npm run test:e2e       # E2E integration tests (requires runtime credentials)

Project Structure

docs/                     # Playbook markdown docs + manifest.json
src/
├── app/                  # Next.js App Router pages
│   ├── dashboard/        # Task kanban board
│   ├── projects/[id]/    # Project detail
│   ├── tasks/            # Task detail + creation (redirects to dashboard)
│   ├── profiles/         # Agent profile gallery + detail + creation
│   ├── documents/        # Document browser
│   ├── workflows/        # Workflow management + blueprints
│   ├── schedules/        # Schedule management
│   ├── costs/            # Cost & usage dashboard
│   ├── playbook/         # Documentation & learning journeys
│   ├── chat/             # Conversational AI (tool catalog)
│   ├── book/             # AI Native Book reader
│   ├── environment/      # Environment control plane
│   ├── inbox/            # Notifications
│   ├── monitor/          # Log streaming
│   └── settings/         # Configuration
├── components/
│   ├── dashboard/        # Homepage widgets + charts
│   ├── tasks/            # Board, cards, panels
│   ├── profiles/         # Profile gallery, detail, form, learned context
│   ├── workflows/        # Workflow UI + blueprints + swarm
│   ├── documents/        # Document browser + upload
│   ├── costs/            # Cost dashboard + filters
│   ├── playbook/         # Playbook docs + journeys + adoption
│   ├── schedules/        # Schedule management
│   ├── monitoring/       # Log viewer
│   ├── chat/             # Chat shell, messages, input composer, tool catalog
│   ├── book/             # Book reader, chapters, reading paths
│   ├── environment/      # Environment dashboard, scanner, templates
│   ├── notifications/    # Inbox + permission actions
│   ├── settings/         # Auth, permissions, budgets, browser tools, data mgmt
│   ├── shared/           # App shell, sidebar
│   └── ui/               # shadcn/ui primitives
└── lib/
    ├── agents/           # Runtime adapters, profiles, learned context, pattern extraction
    ├── db/               # Schema, migrations
    ├── docs/             # Playbook reader, adoption, usage-stage, journey tracker
    ├── documents/        # Preprocessing + context builder
    ├── workflows/        # Engine + types + blueprints
    ├── schedules/        # Scheduler engine + interval parser
    ├── settings/         # Auth, permissions, helpers
    ├── chat/             # Chat engine, context builder, model discovery
    ├── usage/            # Metering ledger + pricing registry
    ├── constants/        # Status transitions, colors
    ├── queries/          # Chart data aggregation
    ├── validators/       # Zod schemas
    └── utils/            # Shared helpers

API Endpoints (58 routes)

Domain Endpoint Method Purpose
Projects /api/projects GET/POST List and create projects
/api/projects/[id] GET/PUT/DELETE Project CRUD
Tasks /api/tasks GET/POST List and create tasks
/api/tasks/[id] GET/PATCH/DELETE Task detail, update, delete
/api/tasks/[id]/execute POST Fire-and-forget task dispatch (202)
/api/tasks/[id]/resume POST Resume failed/cancelled task
/api/tasks/[id]/cancel POST Cancel running task
/api/tasks/[id]/respond POST Human response to agent prompt
/api/tasks/[id]/output GET Task execution output
/api/tasks/[id]/logs GET Task log history
/api/tasks/assist POST AI task assist (description, subtasks, workflow recommendation)
Workflows /api/workflows GET/POST List and create workflows
/api/workflows/[id] GET/PATCH/DELETE Workflow detail, update, delete
/api/workflows/[id]/execute POST Execute workflow
/api/workflows/[id]/status GET Workflow execution status
/api/workflows/[id]/steps/[stepId]/retry POST Retry failed workflow step
/api/workflows/from-assist POST Create workflow from AI assist recommendation
Blueprints /api/blueprints GET/POST List and create blueprints
/api/blueprints/[id] GET/DELETE Blueprint detail and deletion
/api/blueprints/[id]/instantiate POST Create workflow from blueprint
/api/blueprints/import POST Import blueprint from GitHub URL
Documents /api/documents GET List documents with joins
/api/documents/[id] GET/PATCH/DELETE Document detail, metadata, deletion
/api/documents/[id]/file GET Download document file
Uploads /api/uploads POST File upload
/api/uploads/[id] GET/DELETE Upload detail and deletion
/api/uploads/cleanup POST Clean up orphaned uploads
Profiles /api/profiles GET List agent profiles
/api/profiles/[id] GET/PUT/DELETE Profile CRUD
/api/profiles/[id]/test POST Run behavioral tests on a profile
/api/profiles/[id]/context GET/POST/PATCH Learned context: version history, manual add, approve/reject/rollback
/api/profiles/import POST Import profile from GitHub URL
Notifications /api/notifications GET/POST List and create notifications
/api/notifications/[id] PATCH/DELETE Update and delete notification
/api/notifications/mark-all-read POST Mark all notifications as read
/api/notifications/pending-approvals GET Pending approval notifications
/api/notifications/pending-approvals/stream GET SSE stream for pending approvals
Schedules /api/schedules GET/POST Schedule CRUD
/api/schedules/[id] GET/PATCH/DELETE Schedule detail + updates
Settings /api/settings GET/POST General settings
/api/settings/openai GET/POST OpenAI Codex runtime settings
/api/settings/test POST Provider-aware runtime connectivity test
/api/settings/budgets GET/POST Budget configuration
/api/permissions GET/POST/DELETE Tool permission patterns
/api/permissions/presets GET/POST/DELETE Permission preset bundles
Context /api/context/batch POST Batch approve/reject context proposals
Monitoring /api/logs/stream GET SSE agent log stream
Playbook /api/playbook/status GET Playbook adoption status and usage stage
Chat /api/chat/conversations GET/POST List and create conversations
/api/chat/conversations/[id] GET/PATCH/DELETE Conversation detail, update, delete
/api/chat/conversations/[id]/messages GET/POST List messages and send new message (SSE streaming)
/api/chat/models GET Available models with cost tiers
/api/chat/suggested-prompts GET Context-aware suggested prompt categories
/api/chat/conversations/[id]/respond POST Respond to permission or question prompt
Platform /api/command-palette/recent GET Recent command palette items
/api/data/clear POST Clear all data
/api/data/seed POST Seed sample data

Roadmap

MVP — Complete

All 14 features shipped across three layers:

Layer Features
Foundation CLI bootstrap, database schema, app shell
Core Project management, task board, agent integration, inbox notifications, monitoring dashboard
Polish Homepage dashboard, UX fixes, workflow engine, AI task assist, content handling, session management

Post-MVP — 52 features shipped

Category Features
Documents (5) File attachments, preprocessing (5 formats), agent context injection, document browser, output generation
Agent Intelligence (6) Multi-agent routing, autonomous loops, multi-agent swarm, AI assist→workflows, agent self-improvement, workflow context batching
Agent Profiles (2) Agent profile catalog (21 profiles), workflow blueprints (13 templates)
UI Enhancement (13) Ambient approvals, learned context UX, micro-visualizations, command palette, operational surface, profile surface, accessibility, UI density, kanban operations, board persistence, detail view redesign, playbook documentation, workflow UX overhaul
Platform (8) Scheduled prompt loops, tool permissions, provider runtimes, OpenAI Codex runtime, cross-provider profiles, parallel fork/join, tool permission presets, npm publish (deferred)
Runtime Quality (2) SDK runtime hardening, E2E test automation
Governance (3) Usage metering ledger, spend budget guardrails, cost & usage dashboard
Chat (10) Chat data layer, chat engine (5-tier context, CRUD tools), API routes (SSE streaming), UI shell, message rendering (Quick Access pills), input composer (tool catalog, model selector), skill composition (multi-skill with conflict detection), filter namespace (#key:value grammar), pinned + saved searches, conversation templates
Platform Hardening (2) Runtime validation hardening (MCP-tool runtime-id validation with safe fallbacks), upgrade detection (hourly upstream poll + guided merge sessions)
Environment (11) Environment scanner, cache, dashboard, git checkpoint manager, sync engine, project onboarding, templates, cross-project comparison, skill portfolio, health scoring, agent profile from environment
Living Book (5) Content merge (chapters → playbook), author's notes, reading paths, markdown pipeline, self-updating chapters

Planned

Feature Priority Description
Browser Use P1 Chrome DevTools + Playwright MCP integration for browser automation
Workspace Context Awareness P1 Surface cwd, git branch, worktree status to chat agents
Chat Command Mentions P1 Slash commands for tools/actions + @ entity mentions
Task Hierarchy Clarity P1 Distinguish standalone vs workflow-bound tasks
Chat Conversation Persistence P1 URL/localStorage persistence for active conversations
Settings Interactive Controls P2 Slider upgrades for SDK Timeout and Max Turns
Agent Document API Access P2 MCP-based document tools for agent consumption

Contributing

Contributor Setup

git clone https://github.com/manavsehgal/ainative.git && cd ainative && npm install

# Set up one or both runtime credentials
cat > .env.local <<'EOF'
ANTHROPIC_API_KEY=your-anthropic-key
OPENAI_API_KEY=your-openai-key
EOF

# Start the dev server
npm run dev

Pull Requests

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/your-feature)
  3. Make your changes and add tests
  4. Run npm test and npx tsc --noEmit
  5. Submit a pull request

See AGENTS.md for architecture details and development conventions.


License

Licensed under the Apache License 2.0.

Copyright 2025-2026 Manav Sehgal

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AI Business Operating System — run your business with AI agents. Local-first, multi-provider, governed.

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