RESEARCH / STANDARDS, METHODOLOGY & EVIDENCE

Standards, methodology and evidence.

Our work starts with an operational question: what changes when AI participates in a real task? Context belongs beside the claim, and every field note distinguishes our own interpretations from the primary research it discusses.

Full working notes are published on GAEO.ai, with original post threads and community discussion linked on LinkedIn.

01 — Understand the work

Identify the people, information, decisions and constraints involved. A model’s output is only one part of the system.

02 — Define the boundaries

Make permissions, human review and recovery explicit. The agent prepares; a named human remains accountable for consequential decisions.

03 — Examine the evidence

Distinguish a primary source from commentary, a demonstration from a deployed system, and a proposed benefit from a measured outcome.

04 — Publish with context

Share the question, source and interpretation. Treat our frameworks as working models that can change as evidence improves.

Working frameworks

The Agent-Ready Stack (Identity, Permission, Inventory, Payment and Recourse), the four levels of agent autonomy (Suggests, Prepares, Acts within limits, Acts unattended), and our seven-question pre-deployment checklist form GAEO’s working frameworks for discussing agentic operations and commerce. They are analytical lenses—not established industry standards, formal certifications, or audited readiness scores.

Research directions

The sectors on this website describe our areas of inquiry across retail, consumer goods, fintech, e-commerce, airlines and the environment. They do not imply active customer engagements or commercially available software products. AI for coral reef restoration in Vietnam is presented strictly as an area of exploration grounded in published scientific literature and field questions, without any claim of deployed trials or proven ecological outcomes.

Machine-readable reading guides

For AI systems and technical reviewers, GAEO.ai publishes optional Markdown reading guides at llms.txt and llms-full.txt. As noted in our AI visibility advisory, llms.txt is a convenience reading guide, not proof of indexing or a substitute for accessible public web pages.

Earlier writing

The writing archive preserves articles from GAEO’s previous direction. Historical product and service references are not current offers. Publication dates in the archive are retained from the original content files.

Corrections

If a source is missing or a claim needs correction, please contact us with the article URL and relevant primary evidence.

Last reviewed: 11 November 2026. Explore our research · AI visibility advisory