Persona is a persistent, always-on synthetic researcher for the biomedical literature. The problem: science publishes millions of papers a year, but the tools we read it with are amnesiac — a chatbot gives fluent prose with hallucinated citations, forgotten when the session closes; a search tool retrieves but holds no beliefs, never notices contradictions, never re-checks itself, and never acts. Persona's philosophy is to separate a small durable self (interests, a provenance-typed belief-state, memory) from a large disposable swarm of bounded agents that read at scale and are thrown away — scale of reading, discipline of believing. Every belief is typed READ / INFERRED / HUMAN_CONFIRMED / TESTED, so nothing inferred wears the authority of something proven. It runs an autonomous loop: the swarm reads Europe PMC / OpenAlex → a membrane admits claims by provenance → a temporal knowledge graph tracks papers→claims→contradictions over time → the reflecting self forms its own questions and stakes falsifiable hypotheses → an analyst runs real code in a sandbox → results are machine-checked (sympy) or Lean-4-proven → written back, and it escalates to a human exactly when it needs wet-lab judgment. Every claim traces to a real paper+DOI, and a robustness auditor runs statistical forensics in code to give a replication likelihood calibrated on real replication data ("70% means 70%"). In one ~10-minute run on GLP-1 agonists in neurodegeneration it read 20+ papers, machine-checked three mechanism derivations, wrote four cited papers, and flagged and resolved an internal semaglutide/stroke inconsistency — a careful, auditable synthesis, not overclaim. It's a research colleague that compounds: reads more than any human, remembers with provenance, catches fragile papers before you build on them, and routes the one question needing a human to a human. Competitors retrieve and score; none have the persistent self and the acting loop.
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