We back fields we think are ready to move, then check whether they do. Field velocity is that rate of change: how fast talent enters, capital forms, tool costs fall, and output ships. Inflection points are one of the markers we read: dated, falsifiable shifts an accelerating field should produce.
We measure velocity the same way we do the work: as a research program. Whether field acceleration works is itself the open question, tested across all four focus areas.
Learn more about our methodologyPick a focus area. The summary above reads that field’s velocity across the instruments that apply to it; the inflection points below are the specific markers we track, each with its live signal. Tip: click, hold and drag across any spark line to measure the change between two points.
We document the interventions PL R&D runs, then observe how each field changes. The toolkit describes our work; field velocity and inflection points describe the field, not a causal score for PL.
A fixed toolkit we bring to every field. Pick the ones a field is missing, then push.
Fields move with or without PL. We do not claim these interventions directly cause a field to accelerate: field-level attribution is not cleanly identifiable. We name what we run and watch whether the field moves; making that link clearer remains research work.
A hypercert is a verifiable, evolving record of impactful work — what was done, by whom, and where. Each Research Retreat edition is published as one on open infrastructure PL R&D helped originate. Open a card to walk its evidence timeline.
Drag to browse past & upcoming editions · click a card to open its impact claim
Field velocity is the rate a field is moving. We read it through five instrument categories, each able to hold multiple field-specific measures, plus dated, falsifiable markers. Not every measure fits every field. Having no single gating cost does not mean there is no capability curve: comparable cost, scale, quality or capability measures can still be tracked. An unpriced milestone has no market signal; missing data is not evidence of no progress.
These instruments read the research and capital sides of a field. They do not observe invention directly: prototypes, designs, datasets, and negative results largely lack identifiers to count. Closing that gap is itself part of the work.