Travis
Fraser

Hand-grading a big course is slow and uneven, and sending exams to an AI can expose student names. In pre-pilot beta testing across several Haas courses (one has 225 students), with 850+ exams graded to date. It grades to the instructor’s rubric, keeps stored names out of AI requests, and puts every grade in front of the instructor to override.

Most prompt edits ship on a hunch, and fixing one case quietly breaks others. On its first real task it lifted grounded accuracy from 95.6% to 97.7% and cut misread climbs from 12 to zero. A change ships only if it beats the current prompt on data it never saw.

Trail ratings are opinions, and a vision model alone misreads terrain: from pixels it called direction right only 64% of the time. Given the ride’s GPS grade and tuned with Ratchet, 97.7%. Chest-cam frames paired with GPS and accelerometer, so the read starts from measurement.

Rental damage reports are slow and subjective, and an AI that guesses repair costs is a liability. Vision finds the damage; a separate deterministic engine prices it across 62 item types, built from 55+ researched pricing sources, so the model never invents a dollar figure.

A chatbot with private data in context is one jailbreak away from a leak. This one has nothing private to give away: 161 red-team attacks, zero leaks, zero fabrications. It answers only from a public-safe corpus and stores no conversations, bar one narrow security exception.

Most people with a good idea stop at “I can’t code.” These free, self-guided guides get anyone from zero to shipped with AI, no coding. The first goes from a resume to a live site to a chatbot that sounds like you.