According to God of Prompt on Twitter, a structured "Technical Feasibility Assessment" prompt helps founders and PMs rapidly vet AI feature ideas before engineering reviews by forcing concrete answers on feasibility, MVP path, risk areas, and complexity. As reported by the tweet’s author, the prompt asks a senior-architect-style breakdown covering yes or no feasibility with rationale, the fastest MVP using specific libraries or services, explicit performance and security risks, and a blunt complexity rating. According to the post context, AI teams can operationalize this with modern stacks—e.g., pairing LLM inference providers like OpenAI or Anthropic with vector databases such as Pinecone or pgvector, and orchestration libraries like LangChain or LlamaIndex—to quickly validate buildability and reduce cycle time from idea to MVP. As reported by the same source, the practical value is in eliminating vague brainstorming by demanding concrete implementation details, enabling faster alignment in eng syncs and clearer go or no-go decisions for AI features.