intercom fin gave wrong answer: stale content source

TL;DR

Fin is only as current as the content it reads: when help center articles go stale, Fin confidently serves the old answer. Fix the source, not the model: sync Fin to the canonical docs, expire or update stale articles, and audit Fin answers against current content regularly. A wrong answer from Fin is a content operations failure with an AI face on it.

The query

intercom fin gave wrong answer: stale content source

Use this when

• Fin answers contradict current documentation
• Help center updates do not reach Fin's answers
• You are auditing AI answer accuracy
• Debugging wrong Fin responses

Not for

• Configuring Fin's tone or personality
• Writing help center articles
• Fin billing or plans
• Fin handoff configuration

Steps

1. Confirm the source was stale, not the retrieval

Find the article Fin cited and check its last update against the correct answer. If the article was outdated, the fix is content. If the article was current and Fin still answered wrong, the fix is retrieval or grounding. Diagnose before prescribing.

Expected output: stale-source versus retrieval failure classified.

2. Sync Fin to the canonical content source

Point Fin at the single source of truth and ensure it re-indexes on change. Multiple conflicting sources (old KB plus new docs) let Fin pick the wrong one. One canonical source, kept fresh.

Expected output: Fin reading from one current source.

3. Expire or archive outdated articles

Stale articles that remain published are wrong answers waiting to happen. Archive superseded content or mark it clearly outdated. Fin cannot know an article is obsolete unless the corpus says so.

Expected output: no obsolete articles in Fin's corpus.

4. Add a content-freshness SLA for Fin-facing docs

High-traffic topics get reviewed on a schedule: pricing, limits, procedures that change. Assign owners and review dates. Freshness is maintenance, and maintenance needs a schedule or it does not happen.

Expected output: review cadence with owners for key articles.

5. Audit Fin answers against current docs regularly

Sample Fin's answers weekly and check them against the live docs. Track the wrong-answer rate and trace each miss to stale source, bad retrieval, or missing content. The audit is the feedback loop content ops needs.

Expected output: a weekly answer-accuracy audit with categorized misses.

Template: the checklist

Fin stale answers:
[ ] Miss classified: stale source vs retrieval failure
[ ] Fin synced to one canonical, re-indexed source
[ ] Obsolete articles archived or marked outdated
[ ] Freshness SLA with owners on key articles
[ ] Weekly answer audit tracing misses to causes

Variant phrasings

fin answering from old help articles

Steps 1 and 3. Classify, then archive the stale.

ai chatbot wrong answer outdated docs

Steps 2 and 4. Canonical source plus freshness SLA.

fin contradicts current documentation

Steps 1 and 5. Confirm staleness, audit weekly.

Why it happens

Content teams update docs in one place while Fin reads from another: a migrated help center, a duplicated KB, an integration that snapshots content quarterly. Fin answers from its corpus, not from the live site, so every gap between the corpus and reality becomes a confident wrong answer. The AI did its job; the content pipeline did not do its.

Edge cases

• Correct article, wrong Fin answer: retrieval picked a related-but-wrong article. Improve article titles and disambiguation.
• Time-sensitive answers: "current pricing" needs the article updated before the change goes live, not after.
• Multiple locales: each locale's corpus goes stale independently. Audit per locale.
• Answers that were right and became wrong: product changes invalidate answers silently. Tie doc reviews to release notes.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_1YTcpQ8Cov9Ufu10tMPnXA