A daily crypto, finance, and AI vocabulary puzzle covering reserve support, execution quality, retrieval pipelines, and safe agent behavior.
Stablecoin Rails
These terms describe reserve support, verification, cash-out mechanics, and the target price relationship.
- Reserve Assets: Reserve assets are the liquid assets held to support or redeem a token's value.
- Attestation: An attestation is a report or statement that helps verify reserves or other claims.
- Redemption Window: A redemption window is the period when a holder can swap a token back for the asset or value it tracks.
- Peg: A peg is a target price relationship that a stable asset tries to maintain.
Trade Microstructure
These terms describe how orders are placed, how liquidity absorbs size, and why fills can move price.
- Limit Order: A limit order only executes at the specified price or a better one.
- Market Order: A market order executes immediately against the best available liquidity.
- Bid-Ask Spread: The bid-ask spread is the difference between the highest buy price and the lowest sell price.
- Market Impact: Market impact is the price movement caused by a trade's size and how quickly it is executed.
Retrieval Systems
These terms describe representations, storage, ranking, and context limits in search-augmented AI.
EmbeddingVector StoreRerankerContext Window
- Embedding: An embedding is a vector representation that captures the semantic meaning of text or other data.
- Vector Store: A vector store keeps embeddings so nearby items can be found with similarity search.
- Reranker: A reranker reorders candidate matches to improve the quality of retrieved results.
- Context Window: The context window is the amount of text or tokens a model can consider at once.
Agent Guardrails
These terms cover tool use, isolation, memory, and offline testing for agent workflows.
- Tool Calling: Tool calling is the act of invoking a function, API, or service from an AI workflow.
- Sandbox: A sandbox is a controlled environment that limits what code or an agent can affect.
- Memory: Memory is stored context that can help an agent reuse facts or preferences later.
- Evals: Evals are repeatable tests used to measure whether a model or agent behaves as expected.