Show HN: Sensei, documentation agent for coding agents (sensei.eightzerothree.co)

Sensei has emerged as a groundbreaking documentation agent designed specifically for coding agents, enhancing their ability to produce functional code on the first attempt. By efficiently cross-validating information from various authoritative sources, Sensei dramatically reduces context inefficiency—boasting a 20x improvement compared to traditional tools that inundate users with raw documentation. Instead of presenting up to 300,000 tokens of unfiltered data, Sensei distills answers into a concise 2,000-10,000 focused tokens, enabling developers to maintain a clean context for actual coding work. The significance of Sensei for the AI/ML community lies in its sophisticated research methodology, which mimics the investigative prowess of a seasoned engineer. It employs a hierarchical approach to source validation, prioritizing official documentation before diving into source code and real-world implementations. Continuous feedback loops from coding agents allow Sensei to learn and refine its processes based on actual outcomes, ensuring that it continually improves its guidance. Furthermore, its open-source nature and compatibility with private resources position it as a versatile tool for development teams, giving them full control over their documentation searches while promoting trust and transparency in AI-driven coding assistance.