The Large Language Model (LLM)-Based Application Concepts assessment measures the knowledge and skills necessary for entry-level to mid-level information technology professionals to effectively employ Large Language Models within business applications. The test evaluates key areas including Prompt Engineering, API Integration, Context and Conversation Management, Output Handling and Validation, and Tokenization and Cost Management. It also covers topics such as retrieval-augmented generation, model selection, security practices for protecting data submitted to LLM services, and identifying and addressing hallucinations and other output failures that could affect business operations.

The assessment uses Multiple Choice, Multiple Correct Answer, and Essay Composition questions to evaluate candidate skills, with AI-assisted scoring applied to one or more questions. Questions are drawn from a large pool to reduce the risk of cheating, and one or more questions include individual time limits to further deter cheating and improve predictive performance.

The specific attributes measured include:

Following completion, the test produces a Candidate Selection Report that includes an overall score and detailed scores for each attribute.

The Candidate Selection Report also provides expert interview questions that help you probe critical or low-scoring areas, along with a guide for noting your evaluation of the candidate's responses. Consistent use of an interview guide is an important part of gaining better candidate insights and making better hiring decisions.

Note that while the Large Language Model (LLM)-Based Application Concepts assessment is a useful and efficient instrument for confirming a base level of skill or knowledge about this important topic, it is not intended to pinpoint the exact level of candidate or skill. We recommend that skills tests, like this one, be used in parallel with other measurements, such as cognitive ability, job fit, and behavioral history. Each different type of test provides a valuable piece of information you can use when evaluating potential job performance.