AI agent taxonomy: 03
Autonomous AI agents
Autonomous AI agents coordinate multi-step work, choose among permitted actions, use tools, and manage exceptions within defined limits. Agentix Labs treats autonomy as an engineering control—not a marketing label—and increases it only after supervised evidence supports the change.
What bounded autonomy means
A production autonomous agent does not receive unlimited access and a vague objective. It operates inside a defined workflow with budgets, tool permissions, stop conditions, approval gates, escalation rules, and measurable acceptance criteria.
Typical uses
- Multi-stage research and analysis
- Operations workflows that coordinate several business systems
- Exception triage and resolution planning
- Sales, support, or back-office processes with repeatable branches
- Multi-agent systems with a supervising orchestrator
Production controls
- Explicit goals, stop conditions, and action budgets
- Restricted tools and environment boundaries
- Human escalation for ambiguity or high-impact actions
- Step-level traces, cost and latency monitoring
- Scenario evaluation, adversarial tests, and recovery drills
A graduated rollout
The safest path is retrieval first, then supervised task execution, then bounded multi-step autonomy. Each increase in autonomy should be earned through evaluation data, operational ownership, and proven recovery behavior.