PRYSM — Research NotesResearch-grade notes on AI economics, intensity calibration, methodology and reliability. Open benchmarks, cryptographic receipts, fail-safe by design.https://prysm1.com/2026-06-04T18:00:00ZPRYSM Researchresearch@prysm1.comCopyright 2026 PRYSMhttps://prysm1.com/og-card.pnghand-curated · regenerated per releaseHow PRYSM fails safe — four reliability safeguards, test-verifiedtag:prysm1.com,2026:blog/how-prysm-fails-safe2026-06-04T18:00:00Z2026-06-04T18:00:00ZPRYSM EngineeringPRYSM-1 on AIME 2025: methodology, results, and reproducibilitytag:prysm1.com,2026:blog/prysm-1-on-aime-20252026-06-04T00:00:00Z2026-06-04T00:00:00ZPRYSM ResearchWhy frontier accuracy alone doesn't define the best AItag:prysm1.com,2026:blog/frontier-accuracy-is-not-enough2026-05-28T00:00:00Z2026-05-28T00:00:00ZPRYSM ResearchPrysmProof — cryptographic verification of AI executiontag:prysm1.com,2026:blog/prysmproof-cryptographic-verification2026-05-21T00:00:00Z2026-05-21T00:00:00ZPRYSM EngineeringWhy we report uncertainty: single-trial vs N=ktag:prysm1.com,2026:blog/single-trial-vs-uncertainty2026-05-14T00:00:00Z2026-05-14T00:00:00ZPRYSM ResearchBenchmark contamination, and how we handle ittag:prysm1.com,2026:blog/benchmark-contamination2026-05-07T00:00:00Z2026-05-07T00:00:00ZPRYSM ResearchIntensity selection: PRYSM-1's tier frameworktag:prysm1.com,2026:blog/intensity-selection-framework2026-04-30T00:00:00Z2026-04-30T00:00:00ZPRYSM Team