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Talk Freely, Execute Strictly: Schema-Gated Agentic AI for Flexible and Reproducible Scientific Workflows
arXiv β CS AI|Joel Strickland, Arjun Vijeta, Chris Moores, Oliwia Bodek, Bogdan Nenchev, Thomas Whitehead, Charles Phillips, Karl Tassenberg, Gareth Conduit, Ben Pellegrini|
π€AI Summary
Researchers propose a schema-gated orchestration approach to resolve the trade-off between conversational flexibility and deterministic execution in AI-driven scientific workflows. Their analysis of 20 systems reveals no current solution achieves both high flexibility and determinism, but identifies a convergence zone for potential breakthrough architectures.
Key Takeaways
- βLarge language models can translate natural language goals into executable computation but lack the determinism required for scientific workflows.
- βInterviews with 18 experts revealed competing requirements for both conversational flexibility and constrained, deterministic execution.
- βAnalysis of 20 existing systems shows an empirical Pareto front where no system achieves both high flexibility and high determinism.
- βSchema-gated orchestration separates conversational authority from execution authority to potentially resolve this trade-off.
- βMulti-model LLM scoring demonstrated substantial inter-model agreement and could replace human expert panels for architectural assessment.
#large-language-models#scientific-workflows#ai-orchestration#deterministic-execution#schema-gated#workflow-automation#llm-evaluation
Read Original βvia arXiv β CS AI
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