Question 1

Can I run multiple agents for different jobs?

Accepted Answer

Yes. Provision specialist machines from opinionated presets: Hermes for memory and scheduled work, OpenClaw for browser work, Claude Code or Codex for coding tasks. Each preset bundles runtime, model route, memory, and loadout. One dashboard supervises activity, chat, cron, logs, usage, and artifacts.

Question 2

What is Agent Machines?

Accepted Answer

Agent Machines is the product layer above sandboxes: a control plane that provisions a persistent agent worker as one unit — runtime, model route, skills, MCP, integrations, cron, observation, and fleet management — on the machine provider you choose. Pick Hermes, OpenClaw, Claude Code, or Codex, then pick E2B, Sprites.dev, Dedalus Machines, or Vercel Sandbox. Provision specialist workers from opinionated presets (Hermes, OpenClaw, Claude Code, Codex). Each preset is runtime + model route + memory bundle + loadout, visible from one fleet dashboard. The dashboard supervises the fleet. The long-term control surface is dashboard for humans, MCP/CLI for agent-to-agent orchestration.

Question 3

How is this different from a regular chatbot?

Accepted Answer

A regular chatbot mostly returns messages. Agent Machines gives the agent a machine record, runtime root, terminal, filesystem, logs, usage, cron schedules, sessions, artifacts, and installable tools. State lives with the worker instead of disappearing after one request.

Question 4

Which agents can I run?

Accepted Answer

Hermes, OpenClaw, Claude Code, and Codex are supported. Hermes is the default memory, cron, sessions, and MCP-native runtime. OpenClaw is the computer-use runtime. Claude Code and Codex are task-driven CLIs. All persist state under ~/.agent-machines/.

Question 5

Which providers can host the machine?

Accepted Answer

E2B Sandbox, Sprites.dev, Dedalus Machines, and Vercel Sandbox are live provider implementations. Each plugs into the same MachineProvider abstraction for provision, state, lifecycle, exec, streaming where available, and public URLs where supported.

Question 6

How is this different from a sandbox like E2B or Daytona?

Accepted Answer

Those are machine substrates. Agent Machines is the product layer above them: route to E2B, Sprites.dev, Vercel Sandbox, or Dedalus and get runtime install, loadout, gateway, cron, logs, usage, artifacts, and the browser console in one worker. Provider-specific features like sleep, snapshots, and public URLs are surfaced when the selected lane supports them.

Question 7

How do I get my own machine today?

Accepted Answer

Sign in with Clerk, add provider credentials in /dashboard/setup, pick the agent, provider, spec, and model, then provision the machine record. The browser flow creates the provider machine and stores it in your fleet; the reliable agent bootstrap path is still the matching root CLI deploy command until browser-driven bootstrap lands.

Question 8

What tools and skills come pre-installed?

Accepted Answer

The harness ships 161 SKILL.md files, 27 ranked service routes (MCP → CLI → skills per vendor), 39 MCP catalog entries (2 core + 32 bundled + 4 IDE), 24+ closed-loop CLIs, and 9–23 agent-native tools depending on runtime (Hermes, OpenClaw, Claude Code, Codex). The loadout registry — not static marketing copy — is the source of truth.

Question 9

Is Cursor required?

Accepted Answer

No. Cursor is optional delegation for code edits through cursor-bridge and @cursor/sdk. Without CURSOR_API_KEY, the rest of the machine still runs: chat, files, browser automation, closed-loop tools, skills, cron, memory, dashboard polling, artifacts, and provider lifecycle controls.

Question 10

What is ~/.agent-machines?

Accepted Answer

~/.agent-machines is the unified runtime root for Agent Machines. It holds all agent state -- skills, crons, sessions, logs, MEMORY.md, USER.md, config, chats, and artifacts. The repo checkout at /home/machine/agent-machines is used by reload-from-git.sh to sync knowledge from GitHub.

Question 11

What inference providers are supported?

Accepted Answer

Models route through any OpenAI-compatible /v1 endpoint. The CLI defaults to a vendor-agnostic inference URL; override with DEDALUS_CHAT_BASE_URL or configure model.base_url on the machine. The dashboard stores a model slug per machine.

Question 12

What happens when a machine sleeps?

Accepted Answer

On supported providers, sleep pauses compute while preserving the persistent volume. The next wake resumes from disk: app artifacts, agent runtime state, skills, cron schedules, sessions, and the venv remain available.

Question 13

Where does my data live?

Accepted Answer

Provider credentials and gateway bearers live in Clerk private metadata. Machine state lives on the provider machine under /home/machine, with all agent runtime data and app state under ~/.agent-machines. The public client only sees redacted provider and machine status.

Deep Research

Runtime, route, and tools stay explicit.

The agent page shows what happens next.

Scope

Collect

Synthesize