Dev.to
7/25/2026
The original title is about AI agents handling money and the need for proper instrumentation. Let me rewrite this for a mobile feed.
Original: When Your AI Agent Handles Money, "It Worked" Isn't Good Enough
Short summary
The author built Weft, an autonomous milestone verifier where three AI agents stake ETH, gather on-chain evidence, and execute consensus verdicts. They share hard-won lessons on instrumenting the system with OpenTelemetry and SigNoz — tracing system boundaries (peer broadcasts, RPC calls, FHE operations) rather than internal logic, setting aggressive span attributes for queryability, and using alerts to catch silent regressions like stale indexer data. The key insight: when AI agents handle real money, observability isn't optional — it's the product.
- •Instrument system boundaries (HTTP, RPC, API calls), not internal business logic
- •Set span attributes aggressively to make traces queryable datasets
- •Alert on cycle duration thresholds to catch silent regressions early
Generated with AI, which can make mistakes.
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