Building an Agent That Can't Afford to Be Wrong: Quran Sanity Agent
This is a submission for the Sanity Challenge, Path One: Ship an Agent That Queries Real Content When I first opened the Sanity Challenge announcement, one sentence in the Path One brief immediately grabbed my attention: "Build anything that needs an answer it can't afford to get wrong." That one line defined this entire project. If you ask an AI chatbot for movie recommendations or a recipe, a…
The Sanity Challenge announcement highlighted the importance of creating an AI system that cannot afford to provide incorrect information. This challenge inspired the development of the Quran Sanity Agent, a web research workspace designed specifically for querying real content related to the Quran. The agent is built with a focus on absolute accuracy, ensuring that any information about the Quranic scripture or classical commentary provided by the AI is sourced from verified, structured records in Sanity.
Instead of generating Quranic text or relying on Retrieval-Augmented Generation (RAG) which could still lead to inaccuracies, Quran Sanity Agent ensures that all verses, translations, and scholarly commentaries are anchored to immutable records in Sanity. This approach eliminates the risk of hallucinations, which are common in standard LLMs when asked about religious or classical texts.
The agent treats conflicting historical opinions as structured data, clearly distinguishing between contradictory and complementary positions.
Each verse and commentary card in the application features an interactive citation badge, providing users with detailed information such as the exact Sanity Document ID, the physical book locator, and the raw JSON payload from the Content Lake. This transparency allows users to verify the source of the information and understand the exact data that underpins each query.
If a question falls outside the curated dataset, the agent does not try to fabricate an answer but instead explicitly reports an Evidence Gap, highlighting the limitations of the available sources.
The live application, which is accessible at https://quran-sanity.omar-afifi.com, demonstrates how the agent handles various types of queries. Users can test the system with exact verse integrity, comparative interpretations of verses, and semantic retrieval via Sanity Context MCP. The codebase for Quran Sanity Agent is open-source, providing a transparent and verifiable implementation that adheres to strict standards, ensuring the integrity and reliability of the information provided.
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