AI agents work well until they disagree. When that happens, a few failure modes appear: • Workflows stall • Agents loop indefinitely • Agents override each other Today, the fallback is still human intervention. Some systems are experimenting with guardrails ↓ • Human approval gates A human confirms actions before execution. • Manager agents A coordination layer assigns roles and resolves conflicts. • Standardized rails Shared execution and payment standards (e.g., x402) reduce ambiguity between agents. The real challenge isn’t agent capability. It’s safe failure when coordination breaks. Author: Green But Red 📱 X (Twitter) | 📱 Telegram