Literature Review | behavior.engineering

A literature review is the practice of surveying what has already been written and studied before starting new work — ensuring you build on existing knowledge rather than reinventing it from scratch. In AI behavior work, this means staying current with published research on topics like sycophancy, hallucination, jailbreaking, alignment, and evaluation methodology, as well as reading industry documentation and published model cards. The field moves quickly, and practitioners who don’t read the literature regularly find themselves solving problems that were already solved (or discovering that what they thought was their original idea was documented two years ago). For behavior architects, the literature review habit — checking what’s known before diving in — is a professional discipline that improves both the quality of work and the credibility of recommendations.

Empirical ResearchResearch based on observation and evidence rather than theory alone — drawing conclusions from data collected through experiments or systematic observation.
Alignment ScienceThe research field focused on developing methods, theories, and techniques for making AI systems reliably pursue intended goals and values.
Qualitative ResearchA research approach that seeks to understand phenomena through detailed, interpretive analysis rather than numerical measurement.
Research IterationThe cyclical process of formulating questions, running experiments, analyzing results, and using findings to inform the next round of investigation.
Knowledge SharingThe practice of systematically documenting and distributing behavioral insights, findings, and lessons learned across teams and disciplines.