MaestrIA

My dad is a master carpenter in Chiloé, southern Chile. 30 years on the job, most of them as site foreman, and 8 of those years restoring heritage churches with the Fundación Iglesias Patrimoniales de Chiloé. I am his apprentice and I also run the development and business side of his company, Constructora Patrimonial Chiloé. I built its website (constructorapatrimonialchiloe.cl) with Claude Sonnet a few months ago. The website helps people find him. It does nothing to help a client know whether his quote is fair, whether his diagnosis is correct, or whether the trade showing up is the right one for the problem. In Chile alone, 280,000 construction workers are in the same position (INE, 2025). MaestrIA is what I built so a regular family can get an architect-grade diagnosis for the kind of repair an architect would never come to see. You take a photo, describe the problem in your voice in Chilean Spanish, and say where you live. Claude Opus 4.7 thinks live on screen, draws boxes over the damage as it reasons, names the cause, estimates the work in real units (half a day, two days, not "3.5 hours"), and pulls together a committee of trades that argue on screen until they agree on what to do. A managed agent checks the prices against Chilean retail. A second agent writes the WhatsApp message to the chosen maestro for you: greeting by name, problem summary, materials, ballpark budget, time estimate, link to the full diagnosis. The client stops arriving with "my wall got wet" and starts arriving with a brief. The whole system was measured against my dad. He diagnosed 12 real photos in audio, without seeing the AI. Across 9 dimensions (pathology, material, days of work, CLP cost, severity, honesty under uncertainty, and others), MaestrIA agrees with him 81% of the time. Before integrating his interview into the knowledge base, the score was 74%. Same model, same prompt, same photos. The +7 points are his.