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Glossary / Core concepts

Epistemic Engineering

Epistemic Engineering is the practice of engineering how AI systems handle evidence, uncertainty, sources, justification, and meaning across real workflows. For Hermes Labs, this work happens primarily at the language and runtime layer (prompts, retrieval, memory, policies, rubrics, traces, and tool schemas) rather than in model weights.

How it manifests · In practice

In practice this means auditing and hardening the language and runtime layer where most production failures actually originate: the prompt, the retrieved context, the memory, the policies, the rubric, and the tool schemas, rather than retraining the model.

Evidence: Taxonomy paper