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Most AI tools give you control. Few give you a brake. Trust matters when agents write code or touch data.
I use these three pillars:
Explicit laws. I do not hide rules in prompts. Agents follow a fixed set of laws. Every agent follows the same rules.
A binary security veto. The system says pass or block. No middle ground. Bugs reach production when you accept caveats. It is clean or it does not ship.
An audit trail. Every action leaves a record. You see which agent worked and what it decided. You verify instead of trusting blindly.
I use niche specialists for different tasks. They all follow the same laws and veto.
This adds latency. It requires more code. This is a fair trade for real data. Demos are neat. Production needs brakes.
How do you make AI agents predictable in production?
Source: https://dev.to/alex_gonzaga_342705c8b706/i-put-my-fleet-of-ai-agents-under-a-binary-security-veto-heres-why-4d3a Optional learning community: https://predadores.online/ia-governada