# Augmented LLM

> The foundational agent building block: an LLM wired to retrieval, tools, and memory — where the model decides when to use each.

- **Category**: Agentic AI
- **Subcategory**: Tool Use & Environment
- **Canonical URL**: https://designpattern.fyi/patterns/augmented_llm/

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## Description
**Intent**: Build a reusable agent unit that every higher-level workflow can compose without reinventing the basics.

**Context**: You're building a support assistant, coding agent, or workflow runner. Every team that builds agents ends up wiring the same three capabilities: retrieval, tool calls, and memory. The question is whether you do it ad hoc every time or build a consistent block once.

**Solution**: Wire the model with three model-driven capabilities: (1) **retrieval** queries the model issues against external corpora; (2) **tool calls** the model emits and whose results stream back; (3) **memory** the model reads from and writes to across turns. The model — not surrounding code — decides which to invoke at each step. Chains, routers, orchestrators, and multi-agent loops all compose instances of this block.


## Use Cases
- You need a consistent building block for any agent system.
- The model should choose when to retrieve, call tools, or use memory — not hard-coded logic.
- Higher-level workflows need a uniform unit to compose.





## Trade-offs


### Advantages

- One indivisible building block — higher-level patterns compose it without re-implementing basics.

- Model-driven augmentation adapts to each request; no brittle if-else routing code.

- Provider-agnostic — swap the underlying model without touching the augmentation surface.




### Considerations & Drawbacks

- Easy to underspecify when each augmentation should fire; the model may retrieve when it should tool-call.

- Cost compounds when every block calls all three augmentations on every request.

- Debugging touches three subsystems at once; you need observability across all paths.







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**Reference**: [Original Source](https://www.agentpatternscatalog.org/patterns/augmented-llm/)