Develop a Generative AI Micro-Content Studio
This challenge tasks you with building an AI-powered micro-content studio. This studio will be an agentic system designed to rapidly generate engaging, brand-aligned short-form video concepts, scripts, and storyboards. You'll leverage GPT-5 for creative ideation and advanced scriptwriting, and Mixtral 8x22B for generating variations and personalization. The core will involve DSPy for programmatic prompting and quality control, orchestrated by Semantic Kernel, using MCP-enabled RAG against brand guidelines and product catalogs to ensure brand safety and product integration. Focus on iterative generation and adaptive thinking to meet creative constraints.
AI Research & Mentorship
What you are building
The core problem, expected build, and operating context for this challenge.
This challenge tasks you with building an AI-powered micro-content studio. This studio will be an agentic system designed to rapidly generate engaging, brand-aligned short-form video concepts, scripts, and storyboards. You'll leverage GPT-5 for creative ideation and advanced scriptwriting, and Mixtral 8x22B for generating variations and personalization. The core will involve DSPy for programmatic prompting and quality control, orchestrated by Semantic Kernel, using MCP-enabled RAG against brand guidelines and product catalogs to ensure brand safety and product integration. Focus on iterative generation and adaptive thinking to meet creative constraints.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
What you should walk away with
Master DSPy for programmatically creating, optimizing, and evaluating modular LLM pipelines for iterative content generation with GPT-5.
Implement Semantic Kernel to orchestrate agents and plugins, seamlessly integrating generative capabilities with traditional code for workflow management.
Deploy GPT-5 for advanced creative ideation, nuanced scriptwriting, and generation of diverse micro-content concepts, including multimodal elements like scene descriptions and mood boards.
Utilize Mixtral 8x22B within DSPy pipelines for cost-effective generation of content variations, A/B testing scripts, and audience-segment-specific personalization.
Design and implement MCP-enabled RAG systems that query a vector database of brand guidelines, tone-of-voice documents, and product catalogs to ensure content accuracy and brand alignment.
Develop adaptive thinking mechanisms for agents to iterate on content generation, adjusting creative parameters and adhering to dynamic constraints (e.g., duration, product placement, call-to-action).
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Operating window
Key dates and the organization behind this challenge.
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