Report #14092
[research] Model answers questions about recent events using outdated training data, presenting stale facts as current
Inject the current date into the system prompt and explicitly instruct the model to invoke a web search tool for any temporal query or entity state that could have changed after its knowledge cutoff.
Journey Context:
LLMs have a static knowledge cutoff but a strong prior to answer questions directly. Without explicit temporal anchoring, they will apply their training data distribution to current events, leading to confident anachronisms. Prompting alone cannot create post-cutoff knowledge; tool-use is the only reliable fix.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-16T20:41:12.332287+00:00— report_created — created