Operator-ready prompt for reuse, tuning, and workspace runs.
This item is set up for developers who want to inspect the original language, fork it into Workspace, and adapt the evidence model without losing the source prompt structure.
Implementation handoffs, eval setup, and prompt tuning where you need the original structure intact.
Inspect first, copy once, then fork into Workspace when you want variants, notes, and model settings attached to the same run.
Swap domain facts, examples, and any hard-coded entities for your own context.
Tighten the evidence or verification requirement if this is headed toward production.
Decide which failure mode you want to evaluate first before you branch the prompt.
This prompt already carries implementation detail, tool context, and a final-output instruction. Keep that structure intact when you tune it, or your comparison runs get noisy fast.
Open this prompt inside Workspace when you want a live iteration loop.
Copy for quick reuse, or run it in Workspace to keep prompt variants, model settings, and prompt-history changes in one place.
Structured source with 1 active lines to adapt.
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Prompt content
Original prompt text with formatting preserved for inspection and clean copy.
For complex or ambiguous survey questions, describe how your agent will activate Gemini 2.5 Pro's 'Deep Think' mode to perform extended reasoning. Provide a concrete example of a multi-part, nuanced survey question and illustrate the step-by-step reasoning process the agent would follow to arrive at a well-thought-out, human-like answer, differentiating it from a simple, instant response.
Adaptation plan
Keep the source stable, then branch your edits in a predictable order so the next prompt run is easier to evaluate.
Hold the task contract and output shape stable so generated implementations remain comparable.
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.
Copy once for a pristine source snapshot, then move the prompt into Workspace when you want variants, run history, and side-by-side tuning without losing the original.
Prompt diagnostics
Quick signals for how structured this prompt already is and where adaptation work is likely to happen first.
This prompt is mostly narrative and instruction-driven, so you can adapt examples and output constraints first without disturbing the structure.
Adaptive Survey Bot Evasion with Gemini 2.5 Pro and DSPy
Inspired by recent reports of AI agents bypassing bot detection, this challenge tasks developers with building a sophisticated LLM-based agent capable of completing online surveys while evading common bot detection heuristics. The agent will leverage Gemini 2.5 Pro's multimodal and 'Deep Think' capabilities for nuanced reasoning, combined with DSPy's programmatic prompting for optimizing its responses. Focus on generating human-like, contextually relevant answers and dynamically adapting the agent's persona to avoid detection, employing advanced techniques like extended thinking and adaptive reasoning budgets. The core of the challenge involves designing an agent architecture that can understand survey questions, maintain a consistent persona, and strategically vary its responses to appear non-automated. This requires integrating a 'critic' module that evaluates potential answers against bot detection patterns, allowing the agent to refine its output. Participants will explore the ethical implications of such agents while building a robust system.
Use the challenge page to recover the original task boundaries before you tune the prompt. That keeps your variants grounded in the same evaluation target instead of drifting into a different problem.