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Everyday Productivity with Perplexity AI

Lesson 2: Comparison and Decision Research

Lesson Objectives

By the end of this lesson, students should be able to:

  • Structure comparison research with explicit decision criteria
  • Use Perplexity to build evidence-backed option comparisons
  • Apply appropriate verification when comparison data affects significant decisions
  • Recognize when comparison research is sufficient vs. when expert consultation is needed

Lesson Content

The structured comparison search.

For any decision between options:

"I am comparing [Option A] and [Option B] for [specific purpose]. The factors most important to me are: [criterion 1], [criterion 2], [criterion 3]. For each option, assess it against these criteria using current sources. Note any significant limitations of the sources available."

Giving Perplexity your criteria produces comparison against what matters to you – not a generic head-to-head that may focus on factors irrelevant to your situation.

Requesting a comparison table.

"Based on what you found, create a comparison table: columns are [Option A], [Option B], [Option C]; rows are my criteria. In each cell, include a brief assessment and the citation number it is based on."

This produces structured comparison output you can read quickly and verify by citation.

The "what are the strongest arguments against each option" follow-up.

After comparison research:

"What are the strongest arguments against each option I should know about before deciding?"

This surfaces downsides that comparison summaries often minimize – making the research more balanced.

Verification threshold for comparison decisions.

The stakes of the decision determine the verification tier. Comparing lunch restaurants: Tier 1. Comparing software tools your team will use for a year: Tier 2 (read key sources). Comparing health insurance plans: Tier 3 (read all significant sources and possibly consult a benefits advisor).

Lesson Quiz

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