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AI Search Best Practices: Getting the Most from Large Language Models (LLMs)

LLMs like ChatGPT, Gemini, Claude, and Perplexity AI are revolutionizing how we access and use information. But unlocking their full potential requires new strategies for effective searching, verification, and decision-making. Here are today’s best practices for maximizing accuracy, relevance, and productivity with AI search.

Key Takeaways

  • Be Clear and Specific: Precision in prompts yields more relevant, actionable answers.

  • Ask for Sources: Always request citations or links for important or business-critical queries.

  • Iterate and Refine: Use follow-up questions and clarifications to dig deeper or verify.

  • Cross-Check Results: Compare AI responses with trusted sources or competitor models for validation.

  • Beware of Hallucinations: AI may invent plausible-sounding details; always scrutinize surprising claims.

1. Craft Precise Prompts

AI models respond best to focused, detailed questions. Instead of “How do I improve cash flow?” try,

“What are three proven strategies for improving cash flow for a Canadian SaaS company under $10M in annual revenue?”

Adding context (industry, location, time frame, data points needed) drives better, more tailored answers.

2. Always Request Citations or Sources

For business decisions, compliance, or financial analysis, ask for sources:

“List the top three strategies, and include links to relevant case studies or regulatory guidance.”

If your LLM doesn’t offer source links by default (e.g., ChatGPT, Claude), explicitly request them or compare against a model like Perplexity AI that specializes in citation-backed results.

3. Iterate and Refine with Follow-Up

Don’t settle for a single answer. Use follow-up prompts to clarify, narrow, or expand:

“Can you summarize that using a 5-step checklist?”
“How would these strategies apply to a SaaS company in Ontario?”

This iterative process helps surface more actionable, accurate results.

4. Cross-Check Key Results

For critical or high-stakes topics, cross-reference AI-generated content:

  • Run the same query in two LLMs.

  • Search cited sources directly.

  • Verify facts with official or expert-published materials.

This minimizes risk from AI “hallucinations” (confidently wrong answers) and outdated info.

5. Watch for AI Limitations

AI can sometimes misinterpret context, miss nuances, or fabricate facts, especially with niche, legal, or rapidly changing topics.


Best practice: Use AI search as a starting point, not the final authority, and apply your own judgment before acting on its advice.

Savvy Perspective

AI search is an amplifier for knowledge workers and decision-makers, but it’s not infallible. Treat it as a powerful research assistant: valuable, fast, and broad, but always needing your review and final sign-off.

Conclusion
Harnessing AI search means blending precise prompts, source verification, iterative dialogue, and independent validation. By applying these best practices, you’ll extract maximum value from any LLM and make smarter, safer business decisions.