Trust but Verify

AI is a powerful tool, but treating its output as automatically true is a mistake. Here's how to build verification into your workflow without slowing down.

The Tiered Approach

Not every AI output needs the same level of verification. Match your checking effort to the stakes.

Low stakes (light verification)

Internal brainstorming, draft ideas, formatting tasks. A quick scan for obvious errors is enough.

Medium stakes (moderate verification)

Client-facing content, blog posts, presentations. Verify key claims and statistics. Check that advice is reasonable.

High stakes (thorough verification)

Legal documents, medical information, financial reports, published research. Verify every factual claim against primary sources.

Verification Techniques

Ask for sources

"What sources support the claim you just made about market share?"

If AI provides specific citations, look them up. If it can't provide sources, treat the claim as unverified.

Use internet search

Toggle on Octofy's internet search for factual queries. This grounds responses in real web data rather than relying solely on training data.

Cross-reference models

Send the same factual question to multiple models. If they agree, the information is more likely accurate. If they disagree, investigate further.

Check dates

AI models have knowledge cutoffs. If you're asking about something recent, the model might not know about it or might have outdated information.

Verify numbers

Statistics, percentages, and financial figures are common hallucination targets. Always verify numbers from authoritative sources.

Test with known facts

Before relying on AI for unfamiliar topics, test it with facts you already know. If it gets those wrong, be extra cautious with the rest.

Red Flags to Watch For

• Very specific statistics without a named source
• Academic citations you've never heard of
• Dates and timelines that feel slightly off
• Claims that seem too perfectly aligned with your prompt
• Overly confident language about uncertain topics

Building Good Habits

Fact-checking AI should become automatic, like proofreading before sending an email. It takes a few extra minutes and prevents real problems. The more you do it, the faster your instincts develop for spotting unreliable output.