Originally published on AI Tech Connect.
What you need to know Agent frameworks come and go. The patterns underneath them are durable. Whether you are wiring a planner with the OpenAI Agents SDK in Bengaluru, building a stateful graph in LangGraph for a fintech in London, or rolling your own loop with nothing but an HTTP client, you are almost always assembling the same small set of moves. As of 2026, the working vocabulary that the field has settled on — across practitioner write-ups, vendor documentation and the wider community — names six core agent design patterns. Reflection — the agent critiques and revises its own output before returning it. Tool Use — the agent calls external functions, APIs and data sources, usually in a ReAct-style reason-act-observe loop. Planning — the agent decomposes a goal into ordered sub-tasks…
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