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RAG Pipeline Development Prompt

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Linked challenge: Cybersecurity M&A Due Diligence

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Linked challenge

Cybersecurity M&A Due Diligence

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Develop the LlamaIndex RAG pipeline. Describe the data sources (public company reports, industry news, threat blogs) you will use, the chunking strategy, embedding model choice, and the vector database setup. Explain how agents will query this RAG system to gather context for their analyses, specifically for assessing 'AcmeSec's' past breaches and current security posture.

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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.

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implementation

This prompt is mostly narrative and instruction-driven, so adapt examples and output constraints before you rewrite the structure.

Linked challenge

Cybersecurity M&A Due Diligence

Develop an advanced agent system for automated cybersecurity Mergers & Acquisitions (M&A) due diligence. This challenge focuses on creating a Langroid-orchestrated multi-agent system that leverages GPT-5.2 Pro's extended thinking capabilities to analyze potential acquisition targets. The system will integrate with various external data sources—such as threat intelligence platforms, financial databases, and corporate security reports—through a robust MCP tool integration layer. The system should perform deep dives into a target company's cybersecurity posture, identify potential vulnerabilities, assess compliance risks, and project post-acquisition integration challenges. It will utilize RAG with LlamaIndex to query internal and external knowledge bases, enabling agents to retrieve and synthesize critical information efficiently. Adaptive reasoning budgets will be employed to dynamically allocate computational resources for complex problem-solving, ensuring comprehensive analysis within defined cost parameters.

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