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Implement CrewAI Agents and Tasks

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Linked challenge: Competitive Intelligence: Multi-Agent Strategic Analysis for IPO Readiness

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Linked challenge
Competitive Intelligence: Multi-Agent Strategic Analysis for IPO Readiness

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Implement the CrewAI agents and define their tasks. For each agent, set up their `role`, `goal`, `backstory`, and `verbose` level. Define specific `Task` objects for data gathering, analysis, and synthesis. Initialize GPT-4o as the LLM for your agents (e.g., `llm=ChatOpenAI(model='gpt-4o')`). Provide Python code snippets for setting up agents and tasks, and a basic `Crew` that runs these tasks sequentially or in parallel, ensuring clear output for evaluation.

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.