# Scaffolded agent

**Source:** https://promtable.com/glossary/scaffolded-agent

> A scaffolded agent is built on top of a strong general-purpose framework (LangGraph, OpenAI Agents SDK) that provides the agent loop, tracing, and tool-use plumbing — letting developers focus on the domain logic.

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A scaffolded agent is built on top of a strong general-purpose framework (LangGraph, OpenAI Agents SDK) that provides the agent loop, tracing, and tool-use plumbing — letting developers focus on the domain logic.

Building agents from scratch in 2026 is rarely worth it. Scaffolded agents inherit the framework's agent loop, planner-executor split, checkpoint management, human-in-the-loop hooks, tracing, and tool-use plumbing — and the developer writes the domain-specific tools and prompts. The result: faster development, fewer reliability bugs, easier observability. Best practice is to pick the framework that matches your model (LangGraph for cross-model, OpenAI Agents SDK for OpenAI-native, Claude Agent SDK for Anthropic-native) and to add custom logic only where the framework can't reach.

## When to use

- Any production agent.
- Teams without dedicated agent infrastructure engineering.

## Common mistakes

- Re-inventing the agent loop on top of raw chat APIs.
- Overriding framework behaviour without understanding what you lose (tracing, checkpoints, eval hooks).

## Related terms

- [agent](https://promtable.com/glossary/agent)
- [agent-loop](https://promtable.com/glossary/agent-loop)
- [tool-use](https://promtable.com/glossary/tool-use)
- [evals](https://promtable.com/glossary/evals)

*Last updated: 2026-06-01*
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Original page: https://promtable.com/glossary/scaffolded-agent
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