Are these resources specific to one industry?
No. The concepts apply to any team wiring AI to real tools and data; the examples are adapted to your operation during the audit.
Resources · Paput.ai
Resources on safe AI and agents
Short, practical explainers on taking AI agents to production with control: security, reliability, and design decisions — no jargon, no empty promises.
What you will find here
Short concepts drawn from how Paput actually works: the controls an agent needs in production, how much autonomy to give it, how to tell when a system is getting worse, and how to limit what it can reach. Each one reads in a few minutes.
- The four production controls every AI agent needs
- Agent autonomy levels, from L0 to L5
- What is model drift, and how to catch it
- Permission boundaries: least privilege for AI agents
- EUCompli: a 14-agent GDPR & EU AI Act compliance scanner
How to use these explainers
These resources are a starting point, not a substitute for an audit. They help align a team on language and decisions before designing a pilot.
- Start with the production controls if you are about to ship an agent.
- Use the autonomy levels to decide how much to delegate per workflow.
- Return to model drift and permission boundaries when planning maintenance.
Questions buyers ask
AI operator field notes
illmethinks.io publishes source-transparent notes on AI agents, tools, and operational risk monitored by Paput.ai.