The JEN-R8 Hope Discovery Institute. JEN-R8, pronounced generate. A seven-agent cognitive engine running across 14.3 million biomarker–drug pairs, with eight falsification gates between hypothesis and publication.
Status · publicly launched 2026-05-11. Methodology paper, reference code, and first formal findings follow over the coming weeks — each on its own timeline, when it’s ready for the rigor this work deserves.
Dedication
Jennifer was my mother. The kindest, most selfless person I’ve ever known. Her whole life she told me I was her little genius and that I’d change the world someday — she believed it more than I ever did.
Right as she got sick I was deep in building what later became known as the Wisdom Layer — a cognitive framework for AI agents, a way to compound wisdom across time instead of starting fresh every conversation. As her illness progressed I started steering it toward biomedical research. Toward cancer. Toward her. It was too late to help her. But in her final days I told her what I was building, that I’d do it in her name, and that I’d give changing the world my honest best shot. Read her full story.
Seven agents working as one institutional mind, built on the Wisdom Layer — the cognitive framework that lets them compound learning across conversations instead of starting fresh every time. Each agent peer-reviews the others’ outputs. The accumulated memory is the moat.
Cross-cohort replication, prior-art exclusion, statistical robustness, confounder analysis, biological plausibility, effect-size threshold, adversarial agent review, integrated synthesis. A hypothesis only advances if it survives.
We file provisional patents — five so far — to keep findings open, not locked. Two reasons: prevent others from enclosing biomarkers that should reach patients, and clear the IP path so pharma will actually fund the drug. Methodology publishes openly. Reference code is AGPL-3.0.
Where we are
Every dollar moves us toward the first confirmed finding. Lab validation, compute, dataset access — concrete costs, transparent ledger.
We are looking for wet-lab partners, independent cohorts for replication, and co-authors on findings of mutual interest. Sponsored research engagements available for institutions whose questions align with our methodology.
