Back to Prompt Library
implementation
Optimize with DSPy & Implement Adaptive Thinking
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: AI-Driven Financial Risk & Credit Scoring
Format
Text-first
Lines
1
Sections
1
Linked challenge
AI-Driven Financial Risk & Credit Scoring
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
Refine your DSPy pipeline by adding validation and optimization steps (e.g., `teleprompt` or custom optimizers) to improve the accuracy of financial calculations and risk predictions. Integrate a mechanism for adaptive thinking budgets: for complex 'what-if' scenarios or specific deep dives, activate Gemini 2.5 Pro's 'Deep Think' mode (or simulate its effect with extended processing). Demonstrate this with the `AdaptiveBudgetUtilizationTask`.
Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Hold the task contract and output shape stable so generated implementations remain comparable.
Tune next
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Verify after
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.