Generation

Overview

Generate all possible options for a decision or selection

Steps

Step 1: Clarify generation target

State clearly what options we’re generating for.

• What decision needs options?
• What are we choosing between?
• What level of specificity? (categories vs specific items)

Step 2: Identify option categories

Before generating individual options, map the space of possibilities:

• What dimensions do options vary on? (cost, speed, risk, etc.)
• What categories of solutions exist?
• What domains might have relevant approaches?

Step 3: Generate within each category

For each category:

1. List obvious options (what comes to mind first)
2. List unconventional options (what’s unusual or creative)
3. List extreme options (what if time/money were no object)
4. List cross-domain options (what works in other fields)

Step 4: Cross-pollinate

Look for combinations and variations:

• Can options from different categories be combined?
• Are there variations (bigger/smaller, faster/slower)?
• What would the opposite of common options look like?

Step 5: Check completeness

Review option list for gaps:

• Are any obvious categories missing?
• Did we consider all relevant domains?
• Are constraints artificially limiting us?

Step 6: Compile final list

Merge all options into single list:

1. Combine raw_options and combined_options
2. Remove exact duplicates
3. Add brief description to each
4. Tag with category for later filtering

When to Use

• Generating solution options for a problem
• Brainstorming approaches to a goal
• Listing possible materials, resources, or methods
• Finding all possible paths forward
• At strategy discovery phase in GOSM
• When feeling stuck with only obvious options

Verification

• Option list has breadth (multiple categories represented)
• Unconventional options included (not just obvious choices)
• No premature filtering (options aren’t judged/removed)
• Generation gaps acknowledged (know what might be missing)