Agents and frameworks
Practice this questionWANT TO UNDERSTAND THE CONCEPT FIRST?Learn Agents and frameworks
| Concept | Practical explanation |
|---|---|
| Agent | Bounded decision/action/observation loop toward a goal |
| ReAct | Alternate choosing useful action and observing results |
| Router | Select a narrow permitted route |
| Planner/executor | Propose steps separately from controlled execution |
| Supervisor/handoff | Coordinate specialists / transfer task ownership |
| Reflection/critic | Check and revise a draft with bounded retries |
| Multi-agent | Specialized roles only when evaluations justify coordination |
| LangChain | Useful model, prompt, retrieval, and tool components |
| LangGraph | Explicit state, nodes, transitions, checkpointing, and review/resume |
| MAF | Model-driven agents plus explicit workflows in Microsoft ecosystem |
| OpenAI Agents SDK | Agent-focused tools, runners, and orchestration helpers |
| MCP | Standard integration protocol between AI hosts and external capabilities |
| MCP primitives | Tools act; resources provide context; prompts provide task templates |
LangGraph essentials: nodes return state updates; reducers define merge behavior; edges control next steps; model routes need validation; production needs durable checkpoint storage and authorized threads. An interrupted node can restart, so pre-pause side effects may repeat. Checkpointing does not make external writes atomic.
MCP essentials: host manages model interaction; client implements protocol; server exposes capabilities; business service enforces object/action rights. MCP is not a replacement for REST, model tool calling, or authorization. Review discovery and tool-definition changes.
Adapted from 13_AI.MD · “Agents and frameworks”. Code examples are study fragments. Difficulty and core labels are editorial estimates; version-specific behavior should be checked against your project.