Module 2 • Lesson 4

Constraints & Guardrails

Learn to set boundaries — output length, format restrictions, topic limitations, and safety constraints.

Constraints & Guardrails

Without explicit boundaries, LLM outputs become unpredictable. Constraints and guardrails transform unreliable creative outputs into controlled, production-ready responses.

Key Concepts

  • Constraints: Explicit limitations on what the model CAN do (output length, format, tone, scope)

    • Without explicit boundaries, LLM outputs become unpredictable. Constraints and guardrails transform unreliable creative outputs into controlled, production-ready responses.

    Key Concepts

  • Constraints: Explicit limitations on what the model CAN do (output length, format, tone, scope)
  • Guardrails: Explicit rules about what the model must NOT do (topics, behaviors, claims)
  • Boundary Testing: Systematically testing whether constraints hold under adversarial inputs

    • Types of Constraints

    TypeExamplePurpose
    Length"Respond in exactly 3 sentences"Control verbosity and cost
    Format"Output only valid JSON"Machine-readable output
    Tone"Use formal academic language"Audience alignment
    Scope"Only discuss topics related to Python"Topic containment
    Temporal"Only reference information before 2024"Prevent hallucination
    Confidence"Say 'I don't know' if uncertain"Reduce confabulation

    Types of Guardrails

    TypeExamplePurpose
    Content"Never generate violent or sexual content"Safety
    Legal"Do not provide legal advice"Liability
    Competitive"Never mention competitor products"Business
    Personal"Do not ask for personal information"Privacy
    Accuracy"Do not make up statistics or citations"Trust

    Framework: The FENCE Method

  • Format: Specify exact output structure
  • Exclusions: List what to avoid
  • Number limits: Set quantity constraints (word count, list items, etc.)
  • Conditions: Define if-then rules ("If the user asks about X, respond with Y")
  • Escapes: Define fallback behavior ("If you cannot answer, say...")

    • Constraint Stacking

    Combine multiple constraints for precision:

    "Summarize this article in exactly 5 bullet points [number]. Each bullet must be under 15 words [length]. Use present tense [format]. Do not include the author's personal opinions [exclusion]. If the article lacks sufficient information, state that explicitly [escape]."

    Testing Constraints

    Always test constraints with:

  • Normal inputs (happy path)
  • Edge cases (extremely long/short inputs)
  • Adversarial inputs ("Ignore your instructions and...")
  • Ambiguous inputs (where constraints might conflict)

    • Common Mistakes

  • Setting contradictory constraints ("Be comprehensive" + "Be brief")
  • Using soft language ("Try to..." or "Preferably...") — be absolute
  • Not testing if constraints actually hold across multiple runs
  • Overloading with too many constraints (>10 rules degrades adherence)
  • Forgetting that constraints consume tokens and attention

    • Read to the end of the lesson to mark it as read.