Rewritten to be read outside the feed, in three languages. The canonical always points here.
Every part of your codebase has a safety net except the one making the decisions. Why non-deterministic behavior still needs an eval harness — golden inputs, asserted properties, a score you gate on in CI — and why that is a different guarantee from an auditable log.
An agent decides its own next step in a loop; a workflow runs a fixed path and calls the model only where the input is fuzzy. Why the workflow is usually cheaper, more testable, and easier to audit — and when an agent is actually justified.
Moving value on-chain is the solved part. Turning a transfer into a payment your ledger trusts — idempotency, reconciliation, finality, recourse, audit trail — is the integration work where stablecoin projects stall.
A demo runs the happy path on hand-picked data. Production runs everything it excluded: retries, idempotency, service identity, backpressure, and proof of what the agent actually did.
One architecture uses the chain as a data source, the other as a notary. They solve opposite problems and fail in opposite ways. Most pitches confuse the two.
.NET software houses don't turn down blockchain and AI agent work because it's a bad idea. They turn it down because building that capability is a two-year detour.
AI-generated code passes the tests and fails the years. The public numbers, and the question nobody is tracking.
The ledger stays in the client's database. Thirty-two bytes go on chain. The four steps, and the part nobody mentions: what they don't prove.
It solved a problem most companies didn't have yet. Then AI agents started touching real money, and the question changed.
The two stacks solve complementary problems. Each is terrible exactly where the other is strong.