---
title: "Agents and frameworks"
type: "topic"
url: "https://aifordevs.org/topics/agents"
markdown: "https://aifordevs.org/topics/agents.md"
publisher: "AI for Devs"
license: "https://aifordevs.org/reuse"
attribution: "Credit AI for Devs and link to https://aifordevs.org/topics/agents"
---

# Agents and frameworks

Loops that let a model call tools, keep state, and work toward a goal. Framework comparisons, orchestration patterns, and failure modes you will hit in production.

## Articles

- [LLM evaluation: build an eval suite and gate deploys in CI](https://aifordevs.org/articles/llm-evaluation.md): LLM evaluation, step by step: define failure modes, build a golden dataset, choose metrics, run an offline suite, compare to a baseline, and gate CI. (2026-11-08)
- [What is an AI agent? The loop in code, and where it fails](https://aifordevs.org/articles/what-is-an-ai-agent.md): What is an AI agent? A tested agent loop in TypeScript, run offline against a scripted model, with traces of runaway loops, tool errors, and token growth. (2026-11-08)
- [Context engineering: budget and order the context window](https://aifordevs.org/articles/context-engineering.md): Context engineering is choosing what a model reads on each call. Size each section, order it for prompt caching, trim inputs, and test every layout change. (2026-11-08)
- [What is an MCP server? Build and test one in TypeScript](https://aifordevs.org/articles/build-an-mcp-server.md): What is an MCP server? Build a tested TypeScript one with a confirmed write tool, debug it with MCP Inspector, and apply the spec's security requirements. (2026-11-08)

## Glossary terms

- [A2A](https://aifordevs.org/glossary/a2a.md): A2A (Agent2Agent) is an open protocol, introduced by Google in April 2025, that lets agents built by different vendors discover each other, exchange tasks, and stream results. MCP connects an agent to tools and data, while A2A connects agents to other agents.
- [Agent](https://aifordevs.org/glossary/agent.md): An agent is a program that calls a model in a loop, runs the tools the model requests, and feeds the results back until a stop condition ends the loop. The tools and the stop condition set what the agent can do.
- [Agent loop](https://aifordevs.org/glossary/agent-loop.md): An agent loop is the code that sends the conversation to a model, runs any tool calls in the response, appends the results, and calls the model again. The loop ends when a response contains no tool calls or a limit is reached.
- [Agentic AI](https://aifordevs.org/glossary/agentic-ai.md): Agentic AI is software in which a model's output selects the next step, usually a tool call, instead of a fixed script setting the order of steps. The term covers single coding agents as well as multi-agent systems.
- [Tool calling](https://aifordevs.org/glossary/tool-calling.md): Tool calling is a model returning a structured request to run a function you defined, with arguments, instead of plain text. Your code runs the function and sends the result back, which is how an agent loop reaches systems outside the model.

## Platforms

- [LangGraph](https://aifordevs.org/platforms/langgraph.md): Build agents as stateful graphs with checkpoints, human-in-the-loop steps, and streaming.
- [LangChain](https://aifordevs.org/platforms/langchain.md): Integrations and building blocks for LLM apps: models, retrievers, tools, and agent loops.
- [LlamaIndex](https://aifordevs.org/platforms/llamaindex.md): Framework for agents over your data, with document parsing, indexing, and retrieval built in.
- [CrewAI](https://aifordevs.org/platforms/crewai.md): Python framework for teams of role-based agents and event-driven flows.
- [OpenAI Agents SDK](https://aifordevs.org/platforms/openai-agents-sdk.md): Lightweight SDK for agents with handoffs, guardrails, sessions, and built-in tracing.
- [AI SDK](https://aifordevs.org/platforms/vercel-ai-sdk.md): TypeScript toolkit for streaming text, structured output, and tool calls across many providers.
- [Pydantic AI](https://aifordevs.org/platforms/pydantic-ai.md): Type-safe Python agent framework from the Pydantic team, with validated structured outputs.