Temporal validity in retrieval — how do you handle facts that go stale?

[DomLynch]

A practical question about retrieval design for long-running agents.

Most RAG setups treat stored knowledge as static — you embed it once, retrieve by similarity, done. But agents that run across weeks or months accumulate facts that expire or contradict later information. A few scenarios:

1. User says "my budget is £5k" in January, then "budget increased to £10k" in March. Both are in the index. Which surfaces on retrieval?

2. A stored fact references a product version that no longer exists. No explicit signal it is outdated — the embedding still matches.

3. Seasonal or time-sensitive context ("I am preparing for a conference next week") that is meaningless three weeks later.

Curious how people are handling this in practice with LlamaIndex. A few approaches I have seen:

• Timestamp metadata + recency bias in scoring
• Explicit invalidation on write (overwrite old nodes)
• Graph-based approaches where newer edges supersede older ones

Is there a recommended pattern here, or is this mostly left to the application layer? Would be useful to understand what primitives LlamaIndex exposes that are relevant.