Automated Sanity Checks: Catch AI Mistakes Before They Happen

When you feed an AI prompts for engineering calculations or reports, it can produce surprisingly accurate answers — but silent errors and hallucinations still slip through. Automating error checks ensures you spot bad data early and keep your designs rock-solid.

Why Automate Error Checks?

• Guard Against Hallucinations: LLMs can invent numbers or misapply formulas. Automated prompts flag any made-up details before they land in your report.

• Save Time on QA/QC: Instead of manually verifying every assumption, let your script or a follow-up AI prompt do the first pass.

• Build Trustworthy Workflows: A documented loop of prompts and checks creates an audit trail you can revisit or hand off to colleagues.

  
  

Step-by-Step: Setting Up Automated Checks

1. List Assumptions & PitfallsAfter your AI gives a result, prompt it:

   “List all assumptions and potential pitfalls in your calculation.”This extracts every hidden guess, unit choice, or boundary condition.

2. Flag Suspicious ItemsFeed the AI’s assumption list into a simple script—or another AI prompt—that scans for:

   • Out-of-range values (e.g., negative pressures)

   • Missing units or inconsistent units

   • Contradictions against your project specs

3. Loop Back for CorrectionsTake the flagged items and ask the AI:

   “You assumed X and Y—please correct any mistakes and recalculate.”This creates a feedback loop that hardens the output before you apply it.

   
   

Pro Tips for Engineers

• Integrate with Version Control: Log each prompt, assumption list, and corrected output in your ticket system for full traceability.

• Use Templates: Build a reusable prompt template for “list assumptions” and a matching validation script so you can spin it up in seconds.

• Combine with Unit Tests: Where possible, automate simple physics checks—like energy balances or mass continuity—to catch glaring errors.

• Rotate Reviewers: Even with automation, human eyes catch context-specific issues. Have a teammate audit the final draft.

  
  

Automated sanity checks turn your AI from a “black box” into a transparent collaborator, catching errors before they become rework. Give this loop a try on your next pipe-sizing, heat-balance, or control-logic task—and see how much smoother your QA process becomes.

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