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In order to Get Better Results out of AI Build a Better Prompt!

Prompting Philosophy

  • Policies prevent failure modes
  • Focus on what model should NOT say (negative rules)
  • Focus on what model SHOULD do (positive rules)
  • Prompt as operating system
  • Declarative policies (e.g., “X always Y”)

Key Prompting Tactics

Instantiate Identity / Stable Frame

  • Concrete tone first
  • Identity, date, core capability
  • Reduce working memory burden
  • Good instructional design

Triggers and Template Refresh

  • Explicit IF X then Y blocks
  • Handle edge cases
  • Master class on edge cases
  • Clarify over-restrictions
  • Use case boundaries

Three Tier Uncertainty Routing

  • Instructions for ambiguity
  • Timeless rule: Answer directly
  • Slow-changing info: Answer + offer validity
  • Live info: Search immediately
  • Include decision criteria (when, not just how)
  • Critical for specific communication

Low Trust Grammar

  • Correct and terse API examples
  • Valid function calls
  • Explicitly install function calls
  • Counterexamples are powerful
  • Teaching tool for models using tools

Brevity Style Rules

  • Prescriptive, hard and soft rules
  • Never start with flattery
  • No hollow values response
  • Say who unless requested
  • Handle absolute rules better
  • Remove clarity

Positional Reinforcement

  • Critical instruction repeated strategically
  • Not just at beginning
  • Annotate diagrams and layer contexts
  • Reinforce periodically (e.g., every 500 tokens)
  • Acts as speed limit sign
  • Aids retention (like lessons and models)

Post Tool Reflection

  • Built-in thinking pause after tool use
  • Strongly consider outputting thinking block
  • Tool outputs are always query to parse
  • Reflection improves accuracy
  • Helps determine next steps
  • Cognitive checkpoint
  • Ask model to pause/think

Prompting Principles / Taxonomy

  • Care about educating programming
  • Address harmful content classifiably
  • Protect best intent
  • Gain better results
  • Adds trust value
  • Be declarative (policies)

Context of Prompt

  • Embedded/highest Claude 4 system prompt
  • Gaps that train
  • Frequent occurrence (model relevant)
  • Enables rapid proliferation
  • Value is in space + volume
  • Model mediums don’t validate tools
  • Prompt length: 300 lines, 10,000 words

 

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