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Set Up and Run Optimization Simulation
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: Dynamic Ad Pricing & Inventory Optimization
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Linked challenge
Dynamic Ad Pricing & Inventory Optimization
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
Create a simulation environment that mimics market fluctuations and ad requests. Run your CrewAI agent system within this simulation over multiple cycles (e.g., several simulated days or weeks). Collect detailed logs of agent decisions and the resulting simulated revenue and fill rates. Compare against a baseline (e.g., static pricing).
Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Preserve the rubric, target behavior, and pass-fail criteria as the baseline for evaluation.
Tune next
Adjust fixtures, mocks, and thresholds to the system under test instead of weakening the assertions.
Verify after
Make sure the prompt catches regressions instead of just mirroring the happy-path examples.