Aug 18, 2026

Stablecoin Plumbing, Order Book Signals, Agent Control, and Serving Economics

An educational crypto, finance, and AI vocabulary puzzle about backing, market quotes, agent guardrails, and inference efficiency.

Stablecoin Plumbing

These terms cover creation, backing, redemption, and the target value itself.

  • Mint: Minting is the process of creating new units of a token under the rules of a protocol or issuer.
  • Reserve: A reserve is the asset pool held to support a token, liability, or redemption claim.
  • Redemption: Redemption is the process of exchanging a token or claim for the underlying value it represents.
  • Peg: A peg is the target value a stable asset tries to track, often one U.S. dollar.

Order Book Signals

These terms cover the best prices, the gap between them, and available size.

BidAskSpreadDepth
  • Bid: A bid is the highest price a buyer is currently willing to pay in the market.
  • Ask: An ask is the lowest price a seller is currently willing to accept in the market.
  • Spread: The spread is the difference between the best bid and the best ask.
  • Depth: Depth is the amount of buy and sell interest available around the current price.

Agent Control Plane

These terms cover calling tools, isolation, human approval, and logging.

  • Tool Calling: Tool calling lets an AI agent request a function, API call, or other external action to complete a task.
  • Sandbox: A sandbox is a restricted environment that limits what an agent or program can access or change.
  • Approval: Approval is a checkpoint where a human reviews and authorizes a risky or important action.
  • Audit Trail: An audit trail is a log that records what happened, when it happened, and who or what triggered it.

Model Serving Economics

These terms cover delay, work rate, grouped requests, and reduced precision.

  • Latency: Latency is the delay between a request and the start or completion of a response.
  • Throughput: Throughput is the amount of work a system can process in a given time period.
  • Batching: Batching groups multiple inputs or requests together to improve efficiency.
  • Quantization: Quantization reduces numerical precision to lower memory use and speed up inference.