Language model

As explained in Building Reliable AI Systems

A model that represents patterns in language to predict or generate sequences of text.

A language model represents patterns in language to understand prompts and generate text, but a standalone model cannot connect to live systems or perform real-world actions. Asked to find a flight, it may suggest airlines without checking schedules or booking. section 6.0

Figure 6.1 Core differences between a standalone LLM and AI agent

Compare the language capabilities of a standalone model with the tools and actions an agent adds. section 6.0

Agents make language models actionable by adding tools and workflow control. In multi-agent systems, specialized agents can divide image understanding, product search, and policy lookup; a single model handling all three may become inconsistent as irrelevant context accumulates. section 6.0 section 8.0

How Building Reliable AI Systems covers it

How deep it goes

Defines its practical role and production limits, but does not explain model internals or training.

Examples

Uses flight search and booking, plus a customer request combining image understanding, product search, and return-policy lookup.

What you can do after

Evaluate standalone language models by distinguishing text understanding and generation from external action.

How it connects

Connects language models to AI agents, external tools, APIs, databases, and multi-agent systems.

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Compare how 67 books explain language model →

Related concepts

• retrieval-augmented generationused by · Retrieval-augmented generation is a technique that retrieves relevant information from external sources and supplies it as context to a generative model when producing an output.
• promptused by · An input, typically containing instructions or context, supplied to an artificial-intelligence model to guide or elicit its output.
• AI agentused by · An AI agent is a computational system that uses artificial intelligence to interpret information, select actions, and pursue goals through interaction with an environment.
• generationproduces · Generation is the computational production of outputs from supplied inputs or context, often by applying a model to produce predictions or new content.
• ChatGPTincludes · ChatGPT is OpenAI’s conversational AI service, which lets users interact with generative AI models and related tools through natural-language prompts.
• machine learningkind of · Machine learning is a field of computational methods in which systems learn patterns or relationships from data to make predictions, decisions, or other outputs.

This explainer was generated by Manning's knowledge graph from the text of Building Reliable AI Systems. The section links point to the parts of the book it draws on.