Mission Control
Track every mission, stage and agent in one place.
Local-first agent orchestration
Shadow OS
Multi-Agent Operating System
Turn one task into a planned, delegated and remembered mission.
Shadow OS coordinates AI agents, tracks every step, writes memory and delivers the final report.
Powered by OpenClawLocal-firstTelegram-readyObsidian-native
Currently in development. Public alpha coming soon.
runtime
OpenClaw
state
durable
memory
Obsidian
shadow.task.lifecyclelive
Mission
one clear task
01
Plan
steps and owners
02
Agents
specialized execution
03
Memory
Obsidian updates
04
Report
final output
05
Mission Control
Mission Control for AI agents.
See every mission, stage, agent, subtask, memory update and report in one place.
Mission state
Stage, progress, blockers and next action.
Agent activity
Planner, operator, memory and browser roles.
Live record
Events, subtasks and reports stay visible.
Product preview
alpha buildmissionsagentstimelinememoryreports
The Problem
AI agents are powerful.
Real work still needs supervision.
The pain behind real agent work
Long-running agent work needs visibility, memory and a place where progress becomes durable.
01
You lose track of long-running tasks.
Long-running tasks disappear into chat history.
02
You cannot see what agents actually did.
Actions, handoffs and decisions are hard to inspect after the fact.
03
Useful decisions are forgotten.
Good findings get buried unless someone manually turns them into memory.
04
Multi-step work requires manual babysitting.
You keep prompting, checking, copying context and asking for follow-ups.
05
There is no single source of truth.
Plans, progress, memory and final outputs are split across tools.
The Solution
Mission execution for
autonomous agents.
Shadow OS gives agent work a place to live: missions, stages, agent roles, memory writes and reports that stay visible after the chat is gone.
Durable Tasks
Missions survive refreshes, failures and restarts.
Agent Orchestration
Planner, operator and specialist agents work together.
Memory
Important outcomes are written into Obsidian.
Reports
Every mission ends with a useful output.
Remote Control
Start missions and receive updates through Telegram.
How It Works
What happens when you give Shadow a task?
Shadow turns one request into a mission with a plan, agent execution, memory updates and a final report.
01
Capture mission
One request becomes a tracked mission with a clear output.
02
Plan
Shadow breaks the mission into visible stages.
03
Delegate
Planner, operator and specialists get their roles.
04
Execute
Agents work through subtasks while progress is recorded.
05
Remember
Useful decisions and outcomes are written into Obsidian.
06
Report
The mission ends with a useful output and readable record.
Different layer
Why not just use ChatGPT?
ChatGPT is great for conversation. Shadow OS is for mission execution around agents, state, memory and reporting.
ChatGPT
conversation
manual follow-up
temporary context
one assistant
no durable mission state
Shadow OS
mission execution
planner + agents
event timeline
Obsidian memory
Telegram reports
Development Updates
Follow the build as it becomes real.
A public development log for shipped work, current milestones and the next visible pieces of Shadow OS.
View Updates2026-06-07Shipped
Mission Control interface added
Mission Control now has a real product surface for viewing missions, progress, agents, blockers, orchestration and live activity.
Mission ControlCore UIAgents
2026-06-07Shipped
Landing page, waitlist and analytics foundation
Public Shadow OS landing page is live with waitlist capture, Google Analytics, SEO metadata and production domain configuration.
WebsiteWaitlistSEO
2026-06-06Shipped
Public build channels connected
GitHub, Instagram and TikTok links were added so people can follow the build across code, notes and short updates.
GitHubInstagramTikTok
Use Cases
Missions worth tracking.
Shadow OS gives long-running agent work a place to run, report and become memory.
Research missions
Turn research into a mission with agents, notes, memory writes and a final report.
Codebase work
Coordinate reviews, refactors, tests and documentation with visible task state.
Durable workflows
Keep multi-step agent work alive across refreshes, failures and restarts.
Remote reporting
Receive mission updates and final outputs through Telegram when you are away.
Architecture
Local-First Architecture
for AI Agents
Shadow OS does not replace OpenClaw — it completes it. As the product layer above the runtime, Shadow OS adds durable task state, orchestration policy, event timelines, memory routing, and multi-channel reporting. Your AI infrastructure stays local, auditable, and fully under your control.
User Interfaces
Terminal, voice, task views and Telegram commands.
Shadow Core
Plans, delegates, supervises, records events and writes memory.
OpenClaw Adapter
A clean boundary for CLI and gateway runtime operations.
OpenClaw Runtime
Agents, sessions, channels, models, cron, plugins and secrets.
Attached systems
Connected through Shadow Core policy.
Memory
Curated long-term state
Telegram
Remote command and reporting
Obsidian
Canonical knowledge vault
Tools
MCP-shaped tool contracts
task.created -> task.plan.completed -> task.subagent.assigned -> memory.write.completed -> notification.sent
Building In Public
Built in public.
Shadow OS started as a personal system for managing autonomous agents. Now it is becoming a product for builders who want more control over AI workflows.
Follow the build. Join early access.
Done
Architecture
Core UI
Mission Control
Agent Profiles
OpenClaw Adapter
In Progress
Real planner execution
Mission archive
Obsidian task ledger
Telegram reports
Next
Voice
Browser automation
Public alpha
FAQ
Frequently Asked Questions
Everything you need to know about Shadow OS, AI agent orchestration, and how to get started.
AI agent orchestration is the process of coordinating multiple AI agents to work together on complex tasks. Instead of one agent trying to do everything, an orchestration layer like Shadow OS delegates work to specialized agents, tracks progress, handles failures, and assembles results.
ChatGPT and Claude are individual AI models accessed through chat. Shadow OS sits above AI models and manages them as a team — assigning tasks, tracking state, retrying failures, writing memory, and reporting results. It is the operating system that makes AI agents reliable.
Yes. Shadow OS is local-first by design. Your task history, agent memory, and knowledge vault stay on your machine in Obsidian-compatible markdown files. Nothing is sent to external servers unless you explicitly configure an integration.
OpenClaw is the open-source runtime that Shadow OS is built on. It provides the foundational infrastructure for running AI agents — sessions, channels, model connectors, plugins, and tool schemas. Shadow OS adds the orchestration, memory, and user experience layers on top.
Shadow OS is in active development and being built in public. Join the waitlist to get early access when the first usable build is ready. Follow progress on GitHub, Instagram, and TikTok.
The initial release is designed for developers and power users who work with AI agents. Over time, Shadow OS will become accessible to broader audiences through natural language interfaces, voice commands, and Telegram-based interaction.
Follow The Build
Watch Shadow OS take shape.
Follow the public build across code, product notes and short updates. The waitlist is still the main path for early access.
Waitlist
Be first to test Shadow OS.
Join the early access list and get notified when the first public alpha is ready.
local-first / durable tasks / Obsidian memory / Telegram reporting