Scoped AI Employees For Recurring Work

Stop buying apps.
Install the employee that fixes the leak.

One bounded job. Clear gates. Continuous learning. No vague AI theatre.

I audit the role, build a scoped AI employee inside the tools the team already uses, define permissions and approval gates, test it on representative work, and manage continuous learning with controlled review.

Find the first employee →

Two Install Paths

Same role automation. Choose the operating shape.

This page works for both buyers: teams that want Autoage to handle the role as an AI Employee, and AI-native teams that already use Claude Code, Codex, or an internal AI OS and want the role installed as a pack they can operate.

AI Employee

Managed

Best when you want the outcome handled without operating the AI layer yourself. Autoage scopes the job, builds the employee, helps run launch and ramp, monitors the work, and keeps risky edges behind approval gates.

  • Owns: day-to-day role execution and improvement rhythm.
  • You review: approvals, exceptions, results, and commercial decisions.
  • Good for: teams that want capacity without becoming AI operators.

Role Pack

Owned OS

Best when your team already has an AI OS and wants the same role workflow installed inside it. The pack gives your team the role boundary, prompts, SOPs, tool contracts, tests, runbook, logs, and handover record.

  • Owns: the operating logic your internal team can run and extend.
  • You operate: Claude Code, Codex, or your internal AI OS after launch/ramp.
  • Good for: technical teams that want control, portability, and source visibility.

Both paths include scope, acceptance testing, approval gates, docs, launch/ramp support, and a handover path. Ongoing management is optional for either path; the difference is who operates the AI layer after the role is live.

Architecture

How an AI employee thinks.

🧠

Role Boundary

The job statement, owner, trigger, outputs, success metric, and what the employee is not allowed to do.

SOPs And Memory

The source pack, run history, approvals, corrections, failure patterns, and learned rules.

🔧

Tools And Gates

Scoped access, deterministic actions, approval queues, pause rules, logs, and escalation paths.

Time Audit

Find the recurring work leak.

Work-Leak Audit

Find recurring work that is leaking time, margin, follow-up, reporting, or capacity.

Recurring Work Inventory

85% automatable
95% automatable
75% automatable

Continuous Learning, Controlled Review

Improvement comes from every run.

The employee captures learning from approvals, edits, failed tasks, new SOPs, tests, reviews, and measured outcomes as work happens. Daily corrections improve the employee; controlled review decides what gets promoted.

📊

Capture Daily

Collect approvals, edits, failures, exceptions, and owner feedback from every run

💡

Classify

Separate bad context, weak rules, tool errors, and true edge cases

🧪

Promote Safely

Daily corrections improve the employee; review gates decide what becomes a permanent rule

📈

Measure

Track whether the employee removes work and improves the outcome

Compare The Options

What changes when the role is automated.

Full-Time Hire

Human role

  • 3+ month ramp
  • Sick days & PTO
  • Turnover risk
  • Limited to business hours

VA

Managed helper

  • Needs daily management
  • 9-5 only
  • No initiative
  • High turnover

SaaS Tool

Narrow tool

  • Rigid workflows
  • No judgment or context
  • No initiative
  • One narrow function

AI Employee

Managed worker

  • Scoped job
  • Approval gates
  • Action logs
  • Daily learning

FAQ

Common questions.

Why start with the Work-Leak Audit?+
The audit prevents building a clever agent for the wrong job. We find the recurring work leaking time, margin, follow-up, reporting, or capacity before deciding which employee should exist first.
What is the difference between an AI Employee and a Role Pack?+
An AI Employee is the managed path: Autoage helps operate the role after launch. A Role Pack is the owned-OS path: the role boundary, prompts, SOPs, tool contracts, tests, runbook, logs, and handover docs are installed for a team already using Claude Code, Codex, or an internal AI OS. Both can include launch/ramp support, handover, or optional ongoing management.
What's the difference between an AI employee and a chatbot?+
A chatbot answers prompts. An AI Employee owns a bounded recurring job: it watches triggers, uses approved tools, produces agreed outputs, keeps logs, and escalates risky edges to a human owner.
How does improvement actually work?+
The employee captures learning from real operating evidence every run: approvals, edits, failed tasks, new SOPs, tests, performance reviews, and measured outcomes. Daily corrections can improve the employee; controlled review decides what gets promoted, so it is not an unsupervised promise that the employee rewrites the business by itself.
What tools can AI employees connect to?+
The employee can work with the tools needed for the role: CRM, email, Slack, WhatsApp, Sheets, Docs, project boards, reporting surfaces, accounting tools, and APIs where access is approved.
How do you control risk?+
The employee is autonomous inside the job and gated at the edge. External sends, sensitive access, new permissions, publishing, production changes, financial actions, and scope expansion stay gated.
What if my processes change?+
The employee gets updated through the improvement loop. New SOPs, permissions, tools, and edge cases are promoted deliberately instead of letting the system drift silently.
How do I know it's working correctly?+
The employee has logs, approval records, source checks, failure notes, continuous learning records, and controlled review points. Edge cases get flagged instead of hidden.

The first employee is already visible.

Run the audit above to see the work leak. Then let's talk about which employee should be installed first.

Book a work-leak call →