From Vibe-Coding
To Vibe-Everything

Computational chemistry operates entirely on computers with mature open-source tools, generates perfectly reproducible outputs, and has established validation protocols—making it ideal for benchmarking AI agents on real professional tasks.

Bioinformatics uses computation to extract meaningful information from biological data—where analysis and interpretation are the bottleneck, not data generation. Nearly all work is software-mediated with gold-standard benchmarks.

Materials science combines computational modeling and experimental work, offering ideal benchmarks for verifiable AI agent evaluation through auditable, software-native workflows.

Earth science is a workflow-heavy domain with repeatable, deterministic artifacts: acquire data → process/align → analyze → model → evaluate → predict.

Finance is workflow- and evidence-driven, with abundant public data and strict audit/compliance constraints—making it ideal for execution-focused, tool-using AI agent benchmarks.

Game development is a tool-heavy, fully digital domain with abundant verifiable artifacts—ideal for AI agent execution benchmarks across art, engineering, design, QA, and audio workflows.

HR manages the complete employee lifecycle with highly repetitive, rules-driven workflows—making it ideal for AI agent evaluation through payroll calculations, benefits eligibility, and compliance automation.

Neuroimaging is workflow- and evidence-driven: standardized artifacts (BIDS/NIfTI), repeatable QC failure modes, and audit-ready deliverables make it a strong domain for execution-focused agent benchmarks.

Physics research is pipeline-driven and verification-heavy: professional tools produce reproducible artifacts (configs, plots, tables, reports) with clear success criteria.

Robotics workflows often loop from real-world scenes to simulation-ready assets to policy training; the biggest repeatable bottlenecks are tool-driven 3D asset prep and validation.

Supply chain work is highly workflow-driven and artifact-rich (ERP records, POs, invoices, shipment docs), making it a strong fit for deterministic, system-state verification.

Post-production is software-heavy, standard-driven, and produces abundant verifiable artifacts (encoded deliverables, metadata reports, frame comparisons, loudness measurements)—ideal for AI agent evaluation.