In October, software engineer Pietro Miotti was traveling in Peru, reading about Hiram Bingham "discovering" Machu Picchu in 1911, when he had a very 2025 thought: what would Bingham do with today's tools?
He asked several AI agents (Gemini, ChatGPT, Claude and Grok). They all gave the same answer: lidar. Satellite photos of a jungle ruin show only treetops, but lidar fires laser pulses through gaps in the canopy and maps the ground underneath.
Peru turned out to be poorly covered by public lidar, so he pivoted to the Maya region, where roughly 1,200 km2 of lidar strips are publicly available. Then he went to bed and let the agents work.
There was no specialized archaeology model and no custom classifier. The lidar strips were converted into images, and 48 general-purpose agents went through them one by one, following a precise visual guide: look for pyramids, platforms and plazas; filter out natural hills, sinkholes and roads.
By morning they had flagged multiple candidate sites. One hilltop stood out: straight edges and sharp corners on the edge of a cliff - and nature doesn't really do straight lines. Zoomed in, it showed a levelled plaza, an oval pyramid roughly 8-12 m tall, a raised courtyard, and a flat-bottomed hollow that may have been an aguada, a rainwater reservoir.
The agents then checked the raw point cloud to confirm the shapes were in the ground returns, not vegetation artifacts - the site sits under 10-17 m of forest.
The agents drafted a formal report, translated it into Spanish, and Miotti sent it to INAH, Mexico's National Institute of Anthropology and History. On October 21, INAH replied: no registered archaeological site existed at that location. From random thought to an official government reply in under 72 hours.
Then, on November 11, Miotti published an update that every hype headline about this story leaves out: the site had already been mapped in Estrada-Belli et al. (2025). The agents missed that paper during their literature review. So this was a rediscovery - a real site, absent from INAH's register, already present in the academic literature.
Credit to Miotti for correcting his own story at the top of the post. That update is exactly what the agents got wrong, and exactly what a careful human has to catch.
The bottleneck in this kind of work just moved. Scanning is now cheap, parallel and fast - 48 agents can "look" at 1,200 km2 overnight. What is still slow, human and error-prone is verification: the literature check, the official registry, the ground truth. The one clear failure in this project was not the agents' eyes. It was their fact-checking.
Most "AI agents" stories are still about coding. This one is a template for agentic work in any field with open data: chunk the dataset, fan out agents with one narrow job each, spend most of your own effort on verification, and route the result through the proper authorities.
The agents did the looking. A human still had to do the knowing.
Source: Pietro Miotti, "My AI Agents Found an Unmapped Maya Site" (canonical link above). Speculative interpretations of the site's function are the author's, as flagged in his post.
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