Questions about Orchestro.
Updated Read as Markdown ↗
What Factory does, what it costs to run, and where the owner stays involved.
What is Orchestro?
Orchestro is the control plane for autonomous software agents. It maintains persistent AI-agent loops with durable state, work selection, recovery, independent verification, production feedback and learning. Your models supply intelligence and agent harnesses execute; Orchestro keeps the work and evidence connected. Super private beta, primarily used on our own internal projects. The preview is free with hands-on onboarding; users supply their own agents, subscriptions and infrastructure. Public self-service access and broader unattended autonomy remain in development.
Read the product overview →What does ‘Same kernel. Different domain.’ mean?
The Reliability Factory and Content Factory pilot reuse the same durable work, ledger, lifecycle, selector, executor and verifier. Content adds editorial vocabulary, evidence, policy, reviews and publishing adapters. We did not build a second orchestrator. This proves reuse across two domains, not universal domain support.
Read the discovery →Does Factory replace my coding agent?
Factory coordinates your existing coding agents. Codex, Claude Code and Grok have repair-worker adapters. Muse Spark supports mapping proposals, Product Advisor reviews and the Governor runner through the Muse CLI. The project keeps its issue history, evidence and permissions across supported agents.
Check supported roles →What can Factory monitor in an app?
Factory maps product capabilities such as onboarding, an AI assistant, server reliability and analytics. Each capability connects a user goal to screens, services, agents and data. Its success contract defines a metric, population, observation window, baseline, target and guardrails.
Explore app use cases →How does Factory recognize a bug that comes back?
It preserves the confirmed cause, attempted fixes, releases and independent checks. When a later failure reproduces the same cause, the issue can reopen with its earlier repair history attached. A similar complaint alone is not enough to establish recurrence.
Follow the repair example →Can the agent loop keep working for several days?
A configured watch process can keep checking and launching authorized work across days. It needs an awake host, a project schedule, authenticated CLIs and available quota. Individual worker runs still have limits; missing permission or evidence can require owner attention.
Set up scheduled operation →Does Factory require a separate model API bill?
The supported CLI workflow uses your coding-agent subscriptions rather than adding a separate model API billing layer. Model calls still consume subscription quota, and provider terms and limits apply. This is not zero-token or unlimited model execution. The private preview is free; users cover their own agent and infrastructure costs.
Understand providers and quotas →Does accepting an Advisor recommendation deploy a change?
No. An owner decision records intent and rationale. It does not grant code, merge or release permission. An explicit promotion can pass an accepted canonical-problem recommendation into governed intake after checking its scope and current evidence. That promotion still does not start execution.
See current availability →How do you distinguish a successful fix from a product improvement?
An independent check establishes whether the released repair works. Separate capability measurements compare product outcomes using the same definition and population. For example, onboarding activation might move from 62% to a proposed 64%. Before-and-after movement alone does not prove the repair caused it.
See metrics and guardrails →How does a coding agent add work to Factory?
The intake-work skill turns an owner request into a classified batch with acceptance criteria. The intake command validates the batch, checks for duplicates and returns stable backlog and decision IDs. Registering work does not start an agent. The CLI reference includes a complete JSON example.
Copy an intake example →Is Orchestro publicly available?
Orchestro is in private early access with hands-on setup. The owner cockpit and authenticated hosted MCP endpoint are deployed. Content has a public read-only observation; ARVO’s public view is Coming online. Public self-service onboarding and complete ChatGPT / Claude client acceptance remain unfinished.
Read access requirements →Is Orchestro the same as the old MCP package?
Orchestro is the product. The legacy mcp-orchestro package remains a separate implementation with its own repository. Nothing migrates automatically: tasks, data, settings and MCP installations stay where they are.
Name and history →Can I define my own loop?
The original Reliability and Content pilots were manually configured. In the private core, northstar init creates a valid domain manifest from a goal; it does not connect tools or start the loop. Domain Builder / Compiler V1 and agent-guided bootstrap reconcile real capabilities and report ready or not ready. Public self-service onboarding is still in development.
See the loop model →Can Orchestro run marketing campaigns?
A Content Factory pilot runs on danielepelleri.com using the same kernel as Reliability: evidence mining, thesis, articles, reviews, publishing and post-publish checks, with measurement and learning work retained. It is manually configured. General campaign, outbound sales and paid media integrations are still directions to validate, not shipped products.
See the growth loop →Which views are live, historical or illustrative?
Live Factories uses a dedicated public-safe read model with observation times and honest stale or unavailable states. Product illustrations and the retained operating examples use labelled sample data. Their metrics are not customer benchmarks. The Story page identifies real historical cases separately.
Review implementation status →What does the Governor do?
The Governor supervises the Factory within configured authority, evaluates stalls and records interventions. It cannot grant itself new permissions. Owner decisions, unavailable dependencies and insufficient evidence may still require a wait. A resolved blocker and verified resumption are separate facts.
Read the product overview →When does the owner need to step in?
The owner steps in when a recorded gate needs their decision or access: for example strategy, publishing approval or a missing credential. External dependencies and evidence waits are separate categories. The cockpit reports what is blocked and its scope when canonical data supports it; unknown scope is not inferred.
See owner decisions →What happens overnight?
A configured local loop can select and execute authorized work while its host and providers are available. The private cockpit summarizes recorded movement, requests and interruptions. Last durable progress is shown separately from a heartbeat. No activity is invented when the projection is missing or stale.
See current availability →Can I use my existing MCP tools?
Your coding agent can use MCP servers configured in its host, within the project’s permissions. Separately, the private hosted Orchestro MCP endpoint exposes project-scoped reads and bounded owner intent. The local Factory materializes work and verifies results. ChatGPT / Claude client onboarding still needs end-to-end acceptance.
See the MCP workflow →Are Web, Chat, and CLI different systems?
Web, hosted MCP and the local CLI expose the same project model. Cloud requests remain intent until consumed locally; they do not directly mutate the ledger or start a worker. The private cockpit and MCP endpoint are deployed. A complete ChatGPT / Claude owner conversation is not yet claimed as proven.
See chat and integrations →Can I check my Factory from the cloud?
Yes, for configured private projects. The deployed cockpit shows work, requests, owner actions, progress and Blockers & Recoveries, with observation freshness. Execution stays on the project’s Mac or server. Content also has a smaller public read-only projection; ARVO’s public view is Coming online. Public self-service setup remains in development.
See cloud availability →Are the CLI examples real commands?
The examples use actual private-core CLI syntax for status, backlog, Governor, mapping, capability success and Advisor history. Responses are illustrative excerpts using the command output fields, not live project receipts. Run commands from an installed checkout with your own configured project pack.
Read the command setup →