Autonomous AI employees, on the job. Embedded where you and your teammates already work, it starts the moment a need appears and carries the task through to delivery.
- A teammate in the IM chat — after a long thread, just @ it with "turn this into a plan", waker already knows what just happened.
- Autonomously start work on its own — IM messages, schedules, hook events, or API calls, any of these four can trigger it started.
- Multiple wakers, working together — one task, split across roles: they work in parallel, hand off as needed, and review each other — fully traceable.
Three underlying systems let them get real work done on the front line:
- Harness engineering for stable delivery — task state persists, failures recover, and critical steps come with verification and retry. Work spanning hours or days keeps moving toward the goal.
- Your first AI employee — every AI employee has a name, a role, an onboarding date, scoped permissions, and a traceable record. Review what it did and how well it delivered, just like any team member.
- Job skills continuously expand — the built-in role skill library supports custom skills, so digital employee capabilities extend continuously with your needs.
- Acts inside your existing workflows — it works right inside group chats, approvals, docs, sheets, and internal systems, never crossing its permission boundaries.
- Customize for each profession — systematically built for each role: skills, methods, and judgment. Not a generic model wearing a role-shaped prompt.
- Knowledge retention and continuous evolution — you can view, correct, or forget any memory, letting your digital employee forget faulty context. Every collaboration builds shared knowledge.
- Secure, governable, accountable — each role gets its own identity and least-privilege access; sensitive actions require approval and critical actions are fully logged, so automation never crosses your enterprise boundary.
