Nightshift
Full-stack appA platform for cognitive scientists, psychologists, behavioral researchers — anyone who designs experiments with human participants — to prototype, simulate, and analyze studies in minutes instead of weeks.
Both simulation modes are grounded in established cognitive mechanisms from the literature — latent factor models calibrated to published factor loadings, BFS-computed construal probabilities, Big Five trait covariance. A parametric engine gives you instant, deterministic results for rapid iteration. An LLM-as-participant mode uses identity-driven personas built on those same mechanisms, adding process-level richness — chain-of-thought traces, strategy descriptions, and behavior that emerges from who the simulated person is (a phone-checking 19-year-old, a methodical retiree). Both are validated against published findings (Ho et al. Nature 2022, Lin & Ma NComms).
Design
Conversational AI agent proposes experiment variants with three distinct research personas
Simulate
Both modes grounded in cognitive mechanisms from the literature — fast parametric or rich LLM-as-participant
Analyze
Opus-powered analysis chat with heatmaps, factor analysis, and peer-review simulation
Why this matters
Both simulation modes encode real cognitive mechanisms — latent factor models, construal probabilities from path salience, trait covariance — not just statistical noise or prompt engineering
LLM personas are built on those same mechanisms, adding chain-of-thought traces and strategy descriptions researchers can inspect
Construal effect replicates at 85% of published human data (Ho et al. Nature 2022) — and the tool is honest about where it diverges and why