Constraint Systems
Define boundaries and rules that govern agent behavior through hard and soft constraints
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Soft constraints are preferences and goals that guide agent behavior but can be violated when necessary. They define what the agent should do, not what it must do.
Key Characteristics
- •Flexible: Can be violated if other priorities demand it
- •Weighted: Different priorities for different constraints
- •Trade-off aware: Balance competing goals (speed vs quality)
- •Context dependent: Priorities change based on situation
Interactive: Optimization Simulator
Adjust constraint priorities and see how the agent chooses different approaches:
Set Your Priorities (1=Low, 3=High)
Output Quality
Prefer detailed, accurate, well-reasoned responses
Cost Efficiency
Minimize token usage and API costs when possible
Response Speed
Return results quickly to minimize user wait time
Task: Answer customer question about product features
Agent will choose the option that best satisfies your priorities:
GPT-3.5 Turbo (Detailed)
Good answer with reasonable detail, lower cost
GPT-3.5 Turbo (Concise)
Quick answer with essential info, very cheap
GPT-4 Turbo (Detailed)
Comprehensive answer with examples, comparisons, and recommendations
GPT-4 Turbo (Concise)
Clear answer with key points, less elaboration
When Quality is High Priority
Agent chooses detailed responses with advanced models, even if slower or more expensive. Best for complex queries, critical decisions, or expert-level tasks.
When Speed is High Priority
Agent optimizes for fast responses using concise prompts and efficient models. Best for simple queries, real-time interactions, or high-volume scenarios.
Most agent behaviors are soft constraints: cost optimization, response quality, latency targets, verbosity preferences. These create better user experiences without rigid restrictions. Hard constraints prevent disasters; soft constraints enable excellence.