Where Posecode spreads fastest, who pulls hardest, and which engine unlock opens which locked domain. Companion to
../ROADMAP.md(engine capabilities) and../spec/llm-authoring.md(how an LLM authors a movement).
Posecode is "Mermaid for human movement." A person describes a movement in
words; an LLM writes a short .posecode document; the browser validates it,
constrains joint targets to configured ranges, and renders an animated 3D mannequin, producing a
shareable URL. The loop is:
ask an LLM for a movement → it renders → share the link.
This is structurally different from video. A .posecode doc is editable text:
an LLM can generate it, a human can tweak one angle, a clinician can fork it, and
it diffs in version control. Posecode exposes the authored anatomy and constraints
for inspection instead of hiding them in a generated trajectory. Range constraints
are one correctness layer, not a certification of the complete movement. Text also
gives LLMs a structured target that can be parsed, evaluated, and revised.
- LLM-native. The unit of creation is a code block any chat model emits. No studio, no mocap, no rigging.
- Shareable by construction. Every movement is a URL (
posecode-share). A link is the most viral object on the internet. - Agent-native. The
posecode-mcpserver lets Claude/ ChatGPT author, validate, and return a render link inside the chat: the movement appears where the user already is. - Inspectable constraints. Configured ROM limits prevent impossible authored joint rotations, while contact residuals and movement checks expose failures. Health-adjacent uses still require qualified review.
Each domain is rated on four axes:
| Axis | Question |
|---|---|
| Engine-fit today | Does it render cleanly on the v0.1 rig (1 figure, FK, ground-locked feet/hands, no props, no reach-IK)? |
| Customer pull | Is there an acute, recurring need a free shareable demo satisfies? |
| Virality | How naturally does output get shared, embedded, or re-prompted? |
| LLM-authorability | Can a model reliably write correct docs with little context? |
The four domains below score highest on engine-fit × authorability: they work today, so the catalog and the viral loop compound now rather than waiting on the roadmap.
- Customer: anatomy/kinesiology students & instructors, PT/OT/med students, personal-trainer certifications, biology teachers, curious people.
- Aha use case: "What is shoulder abduction?" → an isolated joint sweeps through its plane, labeled. The answer is a moving figure, not a static diagram.
- Viral loop: an LLM answering an anatomy question embeds a Posecode link; teachers paste links into slides/LMS; students re-prompt for the next joint.
- Ships:
shoulder-abduction-demo,hip-flexion-demo,knee-flexion-demo,spine-rotation-demo,elbow-flexion-pronation. - Engine-fit: ★★★★★, single-joint ROM demos are exactly what the rig does.
- Customer: physios, chiros, athletic trainers, and their patients running home-exercise programs; post-op ROM protocols.
- Aha use case: a clinician authors or reviews a movement and hands the patient a link that shows it, with explicit joint targets and validation diagnostics.
- Viral loop: clinician → patient link sharing is high-frequency and trusted; patients forward to family; clinics build reusable libraries.
- Ships:
heel-raises,standing-hamstring-curl,hip-abduction,good-morning(back-health hinge), plus existingneck-rotation,shoulder-stretch. - Engine-fit: ★★★★☆, range constraints support review; bands/balls and lying poses are future (see roadmap).
- Customer: remote workers, HR/wellness programs, ergonomics consultants, "stretch break" apps.
- Aha use case: a recurring "do this every hour" prompt returns a fresh 60-second posture-reset animation.
- Viral loop: Slack/Teams wellness bots posting a daily link; an LLM "stretch break" habit; embeds on internal wikis.
- Ships:
shoulder-rolls,neck-side-stretch,chest-opener,overhead-reach-reset, plus existingposture-reset,spinal-twist. - Engine-fit: ★★★★☆, standing variants render today; true seated needs a chair prop.
- Customer: coaches, dancers/choreographers, martial-arts instructors, general athletes warming up.
- Aha use case (sports/MA): stances, strikes, and warm-up drills as
short, snappy, shareable clips:
front-kick,jab-cross,horse-stance,bow,arm-circles,high-knee-march.
Dance is where the editable-text and visual-scrub foundation provides unique utility:
a dancer or instructor can compose or tweak movement without specialized software,
scrub frame-by-frame through complex footwork, inspect alignment from any camera angle,
and share an interactive 3D link. Note: LLMs are strictly optional—the language,
deterministic parser, range-of-motion validator, and web renderer form the standalone
product foundation (see research/dance-audience-validation.md).
- Customer: dance educators teaching technique, students analyzing alignment, choreographers notating and archiving movement vocabulary, physical therapists.
- Aha use case: "scrub and orbit around a demi-plié or pirouette" → inspect knee tracking, heel contact, and arm lines from any 3D angle at 0.25x speed.
- Primary value drivers:
- Demonstration beyond physical limitations: teachers with injuries or fatigue can demonstrate precise full-range movements.
- Complex movement breakdown: slow scrub and 3D rotation clarify mechanics obscured in 2D video.
- Non-LLM authoring: direct 3D manipulation, text editing in standard IDEs, and preset library composition.
- Status & review: Ballet presets (
demi-plie,eleve,releve,pirouette,chasse) are validated with domain literature and kept experimental pending ongoing peer review. - Engine-fit: ★★★☆☆ today (turnout, plié, elevé, relevé, pirouette, and chassé render); complex aerials (540, grand jeté) and partner work are future.
- Long game: an open, web-native movement specification: unlike proprietary legacy tools (e.g. DanceForms), Posecode documents are open text, git-diffable, and viewable in any browser.
- MCP inside the assistant.
posecode-mcpputs authoring + a render link directly in Claude/ChatGPT: distribution rides on assistants we don't have to build an audience for. - Links as the unit.
posecode-sharemakes every movement a URL; links are forwarded, bookmarked, and embedded. - Gallery grouped by domain. The playground presets carry a
domainand the gallery auto-groups them (Education, Physiotherapy, Desk & posture, Martial arts, Warm-up, Dance, Fitness, Yoga, Mobility) so breadth is visible on the landing page and each domain has an obvious entry point. - Education as top-of-funnel. Anatomy demos answer questions millions already ask LLMs daily; each answer can carry a link.
- Workplace cadence. "Every hour" stretch prompts create recurring, habit-driven link generation.
- Embeds. A link that renders in an iframe drops Posecode into LMSs, clinic portals, and blog posts.
From ../ROADMAP.md, in rough order of leverage:
| Unlock | Domains it opens / deepens | Status |
|---|---|---|
| Hip-hinge | Fitness (deadlift, row, good-morning), back-health physio, martial-arts bow | shipped |
| Reach-to-target IK | Big share of physio (touch toes, cross-body), yoga, prop interaction | shipped |
| Scene props + anchors | Sit-to-stand, box squat, wall sit, dead hang / hanging knee raise | shipped (chair / wall / bar) |
| Lying / seated base poses | Floor yoga, mat Pilates, bed-based rehab (glute bridge, dead bug, cobra) | shipped |
| Hand / finger rig | Grip rehab, expressive gesture, rough finger-spelling | shipped (single-DOF) |
| Two-person + collision | Partner stretches, assisted rehab, contact sports | deferred |
The strategic read: education + physio + desk + dance monetize the rig and build the catalog/virality flywheel. With reach-IK, props, lying/seated poses, and a hand rig now shipped, the roadmap's domains (functional/elderly care, floor yoga, loaded strength, gesture) are reachable today; the remaining frontier is deeper props (load, bands, rings), ROM-constrained reach, and two-person work.
Posecode's range-of-motion values are general literature data, not medical advice. Consult a qualified professional for physiotherapy or exercise prescription.