The Verification Workflow

10 min

What you will learn

Apply a systematic verification process to AI-generated research
Identify the highest-risk claims that need verification first
Use AI to speed up verification itself

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From Trust to Process

The previous lesson explained why you cannot take AI output at face value. This lesson gives you a concrete, step-by-step workflow for verifying AI-generated research. The goal is not to slow you down — it is to give you a systematic process that catches errors quickly so you can move fast with confidence.

Think of verification the way a pilot thinks about a checklist. Pilots do not check every instrument because they expect something to be wrong. They check because the cost of missing something is too high to rely on intuition alone. The same applies to AI-assisted research: most of the time the output is fine, but the times it is not fine can be career-damaging.

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Knowledge check

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What should you verify FIRST in AI-generated research?

Key takeaway

Verify specific facts, statistics, quotes, and citations. Use AI to help organize your verification process, but never skip it.

Practice Exercise

Hands-on practice — do this now to lock in what you learned

Open an AI assistant and try this:

Take any AI-generated research output (or generate one now on a topic you know) and run the verification checklist: 1. Circle every specific number — are they accurate? 2. Check every cited source — does it exist? 3. Flag every causal claim — is the causation real? This exercise builds the muscle memory that makes verification automatic.

Open in ChatGPT

Or try it in:Claude Gemini Perplexity

+10 XP when completed

Write your prompt attempt here (optional)

From Trust to Process