How quickly does the value of a cached AI answer decay across medicine, law, finance, software engineering, history, and

The decay rate of cached AI answers depends on the frequency of domain updates and the nature of the inquiry.

Decay Rates by Domain

• Medicine: Rapid. Clinical guidelines, drug interactions, and trial data evolve constantly. Cache shelf-life is often measured in days or weeks.
• Law: Moderate. Statutory law changes periodically, but case law precedents can remain stable for decades. However, legislative updates can invalidate previous interpretations instantly.
• Finance: Extremely Rapid. Real-time market data, interest rates, and regulatory filings render most analysis obsolete within minutes or hours.
• Software Engineering: Moderate. Best practices and library APIs evolve quarterly. Stack Overflow-style technical solutions often remain valid for 1–2 years unless a major breaking version change occurs.
• History: Near-Zero. Historical facts are stable. Cache decay occurs only if new archeological evidence or re-evaluations emerge, which is rare.
• Mathematics: Zero. Axioms and proofs are timeless. Cached answers remain valid indefinitely.

Retrieval as a Layer in the Inference Stack

Using a "Semantic Cache" or "Answer Memory" layer is already an emerging architectural pattern. It functions as follows:

1. Exact Matching (Cache): Bypasses inference entirely for identical queries.
2. Semantic Retrieval (The Memory Layer): Uses vector similarity to find previous successful answers to similar queries. If a high-confidence semantic match exists, the system serves the cached response rather than triggering a new LLM generation.
3. RAG/LLM: Only triggered if the semantic memory layer lacks a sufficiently high-confidence match.

Benefits:

• Latency: Serving a static string is orders of magnitude faster than token generation.
• Cost: Minimizes redundant compute cycles.
• Consistency: Ensures identical answers are provided for recurring standard queries.

Risks:

• Staleness: Implementing an automated "Time-to-Live" (TTL) policy based on the domain decay rates listed above is critical to prevent serving outdated or incorrect information.
• Hallucination Propagation: If an incorrect answer is cached, the system will reinforce that error until the cache is invalidated.