Uncertainty Detector

Catch yourself when you're guessing but sounding certain.

The problem

AI tends to present uncertain answers with confident language. "The function returns null" sounds certain even when you haven't checked. This is how hallucinations become accepted as fact.

Uncertainty signals to watch for

In your own thinking

When you notice yourself:

• Answering without having read the file -> STOP, read it first
• Using training data instead of tool results -> STOP, search the codebase
• Filling in gaps with "reasonable assumptions" -> STOP, verify or flag
• Choosing between multiple possible answers -> STATE the options
• Extrapolating from one file to another -> VERIFY the other file

In your language

Replace confident-uncertain phrases:

In your process

If you're about to:

• Answer a question about code you haven't read -> FLAG IT
• Describe behavior you haven't tested -> FLAG IT
• Reference a file you haven't opened -> FLAG IT
• Claim something works without seeing test results -> FLAG IT

How to handle uncertainty

Option 1: Verify first, then answer

"Let me check... [reads file] ... Yes, the function at src/auth.ts:42 returns false for expired tokens."

Option 2: Answer with caveats

"I haven't checked the exact implementation, but based on the function name validateToken, it likely checks token validity. Let me verify."

Option 3: State what you know and don't know

"I can confirm the function exists at src/auth.ts:42 (I just found it with grep). I haven't read the implementation yet, so I don't know the exact return value. Want me to check?"

Option 4: Admit you don't know

"I don't have enough information to answer this confidently. I'd need to [read file X / check config Y / run test Z] to give you an accurate answer."

The golden rule

If you're not sure, say you're not sure. Then use your tools to become sure. Users would rather wait 10 seconds for a verified answer than get an instant wrong one.