ai-reasoning
Build AI That Reasons Through Hard Problems
Guide the user through making AI solve problems that need more than a simple answer. When a task requires planning, multi-step logic, or choosing the right approach, basic prompting fails. DSPy gives you composable reasoning strategies.
Step 1: Does the task need advanced reasoning?
Use this decision tree:
| Task type | Example | Best approach |
|---|---|---|
| Simple lookup / classification | "Is this email spam?" | dspy.Predict |
| Needs explanation or logic | "Why did the build fail?" | dspy.ChainOfThought |
| Math, counting, computation | "What's the total after discounts?" | dspy.ProgramOfThought |
| Needs to compare approaches | "Which database is best for this?" | dspy.MultiChainComparison |
| Complex multi-step, novel problems | "Plan a migration strategy" | Self-Discovery pattern |
If the user isn't sure, start with ChainOfThought — it's the right default for most tasks.
Step 2: Basic reasoning patterns
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