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Argument Generation Workflow for 'AI Tax'

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Linked challenge: AI Policy Argument Generation Agent

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Linked challenge

AI Policy Argument Generation Agent

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Orchestrate a workflow where the `PolicyAnalyzer` agent first researches the 'AI tax on synthetic actors' topic using its retrieval tools to gather information from provided documents (representing SAG-AFTRA and Studio perspectives). It should then pass its findings to the `RhetoricGenerator` agent, which, using Claude 3.5 Sonnet, generates a compelling argument for a specified stakeholder (e.g., 'SAG-AFTRA' or 'Studio Executives'). Ensure the `RhetoricGenerator` focuses on the most impactful points and persuasive language.

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

Linked challenge

AI Policy Argument Generation Agent

Develop an advanced AI agent system using the Claude Agents SDK to assist in complex policy negotiations, drawing inspiration from the SAG-AFTRA talks regarding an 'AI tax' on synthetic actors. This challenge requires building a system capable of analyzing diverse policy documents, legal texts, and economic data to generate well-reasoned arguments and counter-arguments for specific stakeholders, such as labor unions and production studios. The core of the solution will be a multi-agent workflow orchestrated by the Claude Agents SDK, leveraging Claude 3.5 Sonnet for its robust reasoning and document understanding capabilities. The agents will be tasked with identifying key points of contention, forecasting potential impacts of proposed policies, and synthesizing persuasive rhetoric. Evaluation of the generated arguments will be conducted using Gentrace, focusing on logical coherence, factual accuracy, and persuasive strength. The system will rely on Azure Blob Storage and Azure Cognitive Search for efficient storage and retrieval of relevant policy documents and background information.

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