10 · Research · product · Jul 2026

STRIAQ

Research and an MVP scope for AI agents in mineral exploration: ingest decades of drilling data, build a geological memory per project, and rank the next targets.

4 of my commits in this codebase[20] Sourcescripts/export-commits.mjsAs of2026-09-26StatusVerifiedAll sources →

The decision

Decompose the ten-x claim

The pitch I started with was "ten times faster mineral processing". A geologist would tear that apart. The speed-up is real, but it lives in the decision loop, from data to decision in hours instead of weeks, not in the rock. So the product is positioned as the Competent Person's exoskeleton: it supports the named expert the reporting codes require, it never replaces them.[16] SourceDownloads/striaq_mvpAs of2026-07-27StatusVerifiedAll sources →

What I built

  • Market research, a competitive map and the positioning.
  • The MVP scope and architecture: legacy data rescue as the entry wedge, an auditable evidence chain, and a critic agent that cannot be bypassed.

What was hard

An industry that is right to be sceptical

Reporting codes require a named Competent Person and no published guidance accepts machine-derived resource estimates. The product had to be designed around that, not against it.

What I learned

  • The strongest positioning removes the buyer's biggest objection before they raise it.

Results

  • Research and MVP package complete. Not yet built as a product.