Rewritten to be read outside the feed, in three languages. The canonical always points here.
Anchoring a hash on-chain is an afternoon of work. What decides whether it was worth anything is the verification path: who checks, with what in their hands, years from now.
Minting a token is the easy tenth of the work. The binding, the redemption path and proof-of-reserve are the product — and where tokenization projects quietly succeed or fail.
Putting a person on the approve button feels like control. Under load, automation bias turns review into a rubber stamp — and the setup keeps no evidence of what was actually checked.
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.
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.