Decisions and Patterns - How Your AI Learns

Two Types of Learning

Decisions: Explicit choices you make. Patterns: Implicit styles your AI detects.

Both compound your intelligence.

Decisions - What You Choose

When you make a choice, your AI asks:

AI:  "You chose Zod over Yup for validation. Should I remember this
      for future projects?"
You: "Yes"

That's it. Next time validation comes up, your AI already knows.

Decisions are explicit. You choose. Your AI remembers. You can change your mind anytime.

More decision examples:

  • "Use FathymAPI for APIs" → AI applies to future API projects
  • "Prefer functional components" → AI writes functional, not class
  • "Test with Deno.test, not Jest" → AI uses native testing
  • "Name files in kebab-case" → AI follows your convention

Patterns - What Your AI Detects

After working with you across sessions, your AI notices consistency:

AI:  "I've noticed you always add error boundaries around async operations.
      Should I apply this pattern automatically?"
You: "Yes"

Patterns are implicit. Your AI observes your work, detects what you do consistently, and proposes making it automatic. You approve what sticks.

Pattern detection examples:

  • Code style: "You always destructure props in function signatures"
  • Architecture: "Your API routes always have input validation, then auth check, then handler"
  • Workflow: "After creating a new file, you always add it to the barrel export"
  • Quality: "You always add error handling before shipping"

The Difference

DecisionsPatterns
HowYou choose explicitlyAI detects from your behavior
WhenAt the moment of choiceAfter observing consistency
Confirmation"Remember this?" - Yes/No"Apply automatically?" - Yes/No
OverrideChange anytimeAlways overridable
SpeedImmediateBuilds over sessions

What You Don't Do

No config files to write. No style guides to maintain. No rules to teach your AI manually.

You just build. Your AI learns from how you work.


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