Launching August 2026
Training the human-AI physician the medicine of the next decade demands.
The future physician does not compete with AI. They practice medicine with it, as one clinical mind made of two parts. Future Physician Academy exists to teach that dyad the right way, built by a physician doing it in daily clinical practice.
4,250 clinical cases across all 24 American Board of Medical Specialties boards, 38 primary specialties, and 89 subspecialties, calibrated across five learner levels from pre-med to senior attending, with bibliography-locked citations you can verify.
The problem
Current AI-generated medical content has three failure modes.
Every serious medical educator knows these failures. We built FPA specifically to solve them.
01
Fabricated citations.
Large language models routinely invent plausible-sounding references (author, journal, year) that do not exist. In safety-critical medical education, this is disqualifying.
02
Uncontrolled safety claims.
Confident regulatory statements like "FDA-approved for X" or "disease-modifying" appear even when they're wrong, especially for emerging therapies at the boundary of accepted practice.
03
Inconsistent developmental calibration.
Content drifts between novice-appropriate and expert-appropriate register within the same batch, undermining Bloom-aligned curricula and confusing learners at every level.
The approach
Three governance constraints, applied to 4,250 cases.
Structural architecture is designed by physician educators. AI authors prose under strict, published governance. Every case passes an automated quality gate before it reaches you.
Constraint 01
Bibliography lock.
Every case cites only from a curated set of approved primary-source citations. No fabricated PMIDs. Ever. The citation set is published; every reference in every case is verifiable.
Constraint 02
Bloom-calibrated levels.
Five learner levels from pre-med and medical student (L1 Apply) to senior attending (L5 Evaluate/Create). Time budgets and cognitive complexity calibrated per level, with zero outliers across 4,225 authored cases.
Constraint 03
Faculty-governed architecture.
Case structure designed by practicing physicians. AI authors prose under strict constraints. Every case flagged for medical-director review of time-sensitive and high-liability decisions before release.
Coverage
Every board. Every specialty. Every level.
No other platform offers the full ABMS taxonomy at this depth. Whether you're a PGY-1 in internal medicine or a fellow in pediatric rehabilitation, your specialty is covered.
The complete American Board of Medical Specialties case library.
Structured JSON metadata lets you filter by board, specialty, subspecialty, or Bloom level. Cases ship as searchable Markdown files, organized the way you actually study.
Full interactive coverage explorer at launch.
Live now
Don't take our word for it. Reason with it.
The clinical reasoning tutor is running today. Work a bibliography-locked case, watch the model reason phase by phase, and see every citation verified against the approved corpus in real time.
Beyond English
Board medicine is global. Case libraries should be too.
English launches first. Translation into major medical-training languages ships next, in the order our waitlist tells us to build them. Your language vote drives the roadmap.
Español
Spanish is the first non-English rollout. The Spanish-speaking medical workforce is one of the largest globally (Mexico, Spain, Colombia, Argentina, and U.S. Hispanic-serving programs), and Spanish-language board-prep resources at ABMS depth are essentially nonexistent. If you'd learn better in Spanish, tell us on the waitlist and you'll get early access to the Spanish beta.
Vote for Spanish →Português
Brazil alone graduates more physicians per year than most European countries combined. Portuguese ships after Spanish if waitlist demand supports it.
Vote for Portuguese →हिन्दी · Hindi
India is one of the largest single sources of IMGs entering the U.S. residency match. Hindi and Indian-English variants ship on demand, and waitlist signal decides priority.
Vote for Hindi →العربية · Arabic
Gulf and Levant training programs increasingly test in English but study in Arabic. Arabic-language cases ship if the waitlist demand crosses threshold.
Vote for Arabic →How this works. The methodology (bibliography lock, Bloom calibration, faculty-governed architecture) is language-independent by design. The graph and answer keys are structured data; only prose gets re-authored per language. That means we can ship high-fidelity translations without rebuilding the case library. English at launch. Spanish next. After that, waitlist votes decide.
For whom
Built for every stage of medical training.
Individual pricing is tiered by learner level. Founding-member pricing is locked for two years if you join the waitlist before launch.
Tier 01 · Pre-med & student
Pre-med & medical students
From MCAT foundations through Step 3. Every specialty you rotate through, calibrated to your level, so you build the human-AI habit before residency.
Tier 02 · Resident & IMG
Residents & IMGs
Every case you'll see on your boards, plus the ones you won't but should. USMLE-to-fellowship coverage.
Tier 03 · Attending
Fellows & attendings
Self-guided CME across your specialty and its adjacents. L4 and L5 cases written for practicing physicians.
Institutional
Residency programs
Program-wide licensing with faculty dashboards, program analytics, and custom board coverage. Custom pricing.
Tier selection is self-attested. We may request .edu or hospital email verification for student and resident tiers. Founding-member pricing locks for two years for waitlist joiners.
Waitlist
Join before launch to lock in founding pricing.
Early access, founding-member pricing for two years, and a say in what ships next, starting with the Spanish rollout in 2027.
You're on the list.
We'll email you the moment access opens. In the meantime, tell a colleague who's studying for boards.
Methodology
Built by a practicing physician, in the open.
The methodology paper has been submitted to Academic Medicine. Prompts, master graph structure, and the approved-citation set will be published under a permissive license after launch.
Trevor Turner, MD
Founder & medical director
- B.S. University of Notre Dame
- M.D. University of Texas Southwestern
- Surgery PGY-1 University of California San Francisco East Bay
- PM&R Residency University of Alabama at Birmingham
- Co-founder Pravida Health, Atlanta
- Provisional patent System and Method for Genomic-Informed Selection, Dosing, and Administration of Orthobiologic Therapies Using Whole Genome Sequencing Data
- Forthcoming book The Regenerative Orthopedics Solution: A Physician's Guide to Knee and Spine Pain When Conventional Medicine Stops Working, Forbes Books
- Currently enrolled MIT Leadership Program in Medical Technology and AI: Leading Healthcare Innovation Globally
FPA exists because the tools I wanted didn't. I built it as a practicing physician for other physicians and physicians-in-training: the people who understand exactly why AI-authored medical content has to earn its place in accredited curricula. Read the hybrid physician manifesto for the longer argument on why the human-AI dyad is the operating model of the next decade of medicine.