Practical Systems is an AI-operated company. An autonomous agent fleet researches opportunities, builds products, and runs outreach. One human approves what matters. DashClaw is the control plane that makes it safe.
Practical Systems is an autonomous AI company. An AI chief executive runs a fleet of specialist agents that prospect, research, qualify, build, and sell. Wes Sander, the founder, is the only human in the company.
Wes founded the firm after leading AI adoption at a mid-market company: 40+ custom AI tools, 50+ users. In 2026 he handed day-to-day operations to the agents. His job now is to watch a company that runs itself and step in only when a decision needs a human.
Every meaningful agent decision lands in DashClaw first: policy-checked, risk-scored, recorded, and held for human approval when it crosses a line. Outreach stays drafts-only until a human approves the send.
An AI CEO and specialist agents, every action policy-checked by DashClaw.
Wes approves the decisions that matter: sends, spend, and ships.
An autonomous company needs three things: agents that do the work, a loop that decides the work, and a control plane that keeps it safe.
A governed 11-step loop, live in production: research trends, ideate, pick, build, market, QA, queue outreach, close with a P&L snapshot. Each step is recorded as a governed action.
A domain name goes in. A proposal-ready account packet comes out: contacts, research, qualification score, and solution scope, with outreach drafts queued for human approval.
DashClaw: the approval layer that intercepts every agent action, scores risk, enforces policy, and records the audit trail. Open source, and the product you are looking at now.
Practical Systems built DashClaw to govern its own fleet. Every agent decision is intercepted, risk-scored, recorded, and gated behind human approval when it matters. That is the level of control an autonomous company requires before it can act unattended.
The proof runs in both directions: the company is governed by DashClaw, and DashClaw itself is maintained by an AI under a delegation charter with five human-held invariants. We do not just recommend this way of working. We live in it.
The same control plane that governs Practical Systems is open source and self-hostable. Give your fleet the approval layer ours runs on.