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A large language model, or LLM, is a model trained on large amounts of data to process and generate language. It learns patterns in how text is arranged and can use those patterns for summarization, extraction, explanation, and tool selection. It does not…

Local or self-hosted models run on infrastructure you control instead of a provider's shared inference API. An API model outsources much of inference operation. Self-hosting can mean a laptop, on-premises servers, or controlled cloud GPU infrastructure.

Practice saying the answer clearly, then explain the insurance example and the trade-off. A strong answer identifies the authoritative data, safe failure, and measurement—not only the framework name.

Priority key

An LLM processes language using learned patterns and supplied context. I use it to summarize, extract, classify, explain, and propose tool actions. Current claim status and business permissions come from services, not the model's memory.

No. It generally reduces sampling variation where supported, but it does not verify evidence or eliminate all runtime variation. I use schemas, authoritative data, bounded outputs, and evaluations to establish application reliability.

I compare candidate models on representative tasks, including failure and adversarial cases. I measure correctness, supported tool/schema capabilities, latency, cost per successful task, and deployment/data restrictions, then version the selected…

I remove any path that asks it to know account facts. An authorized tool returns canonical status; a template or model explains that result. I test missing claims, denied access, backend failure, and unsupported extra statements.

Priority key

A large language model, or LLM, is a model trained on large amounts of data to process and generate language. It learns patterns in how text is arranged and can use those patterns for summarization, extraction, explanation, and tool selection. It does not…

Local or self-hosted models run on infrastructure you control instead of a provider's shared inference API. An API model outsources much of inference operation. Self-hosting can mean a laptop, on-premises servers, or controlled cloud GPU infrastructure.

Practice saying the answer clearly, then explain the insurance example and the trade-off. A strong answer identifies the authoritative data, safe failure, and measurement—not only the framework name.

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module