The Description-Discernment Loop
Refining with AI · 7 min
Mak, CEO of MAKS Enterprises TIPM Rebuilders, demonstrates the Description-Discernment loop — showing how he worked with AI using his domain expertise and judgment.
The Description ↔ Discernment loop
Fluent AI use happens in a tight loop: you describe what you want, the model responds, you discern what's useful, and you describe again — sharper this time. Delegation sets the stage; diligence closes it.
Key takeaways
- Effective Description provides context: explain what your business does, what you're trying to accomplish, and what you specifically need to know.
- Discernment isn't optional: flag specific claims — regulations, pricing data, deadlines — for verification against primary sources.
- The loop is iterative: use what you learn from each response to refine your next prompt.
- AI accelerates research but doesn't replace expertise: you're still the decision-maker applying your own business judgment.
Exercises
Policy and legislation tracking
Practice using Description and Discernment to research regulations, compliance requirements, or industry trends relevant to your small business.
Part I: Self-Reflection
Choose a regulatory or industry area relevant to your business (local zoning laws, licensing requirements, tax changes, labor regulations, industry-specific compliance, etc.) and identify:
- The specific regulation, policy, or trend you want to understand
- Your business context — what you sell or provide, where you operate, who your customers are, and why this topic matters to your operations
- What you need to know — impact on your business model, compliance steps, deadlines, cost implications, or competitive considerations
- Time frame or geographic scope — local, state, or federal? Recent changes in the past year?
Part II: Collaboration
Using the context you identified above, craft a detailed prompt and share it with AI. Then review the response and apply Discernment:
- Identify at least two claims that need verification against official sources (government websites, regulatory bodies, industry associations)
- Note any missing perspectives — for example, did it address how the regulation affects businesses of your size specifically?
- Flag any information that seems outdated, overly general, or that conflates rules from different jurisdictions
Part III: Reflection
Did your initial prompt give AI enough context to be useful? What would you revise for a second attempt? What verification steps would you take before relying on this information to make a business decision?
Stretch goal: Ask AI to track down the original source for one key regulatory claim in its summary — a specific fee, deadline, or threshold — and then go verify it yourself. Compare how accurately the AI represented the source.
Lesson reflection
- How did providing your business context change the quality of AI's research output versus a generic query?
- What verification habits will you build into your workflow when using AI for research?
What's next
In the next lesson, we'll explore the outer loop of Delegation and Diligence by analyzing data with AI.