Building agentic systems can be tricky. A sequential pattern is slower and more expensive. Most frameworks default to it without telling you. 1️⃣ Sequential execution The model calls Tool A, waits for the result, decides to call Tool B, waits, calls Tool C, waits, then synthesizes. Each round trip adds latency and an LLM inference step. Four tools at one second each is four-plus seconds minimum. 2️⃣ Parallel execution The model plans all tool calls in a single inference step, fans them out simultaneously, then synthesizes when all results return. Same four tools, roughly one second total, limited by the slowest tool rather than the sum of all tools. 3️⃣ The tradeoff Parallel requires the model to identify all needed tools before seeing any results. That works when tools are independent. It breaks when Tool B’s input depends on Tool A’s output. Know which situation you’re in. At 10k agent runs per day, the difference between sequential and parallel isn’t a performance footnote. It’s your infrastructure cost and your users’ experience. LangChain, AutoGen, and most frameworks default to sequential. Check your implementation. Independent tools get parallelized. Dependent tools get sequenced. Most production tasks are a mix of both. Save this before you build your next agent. 💾 #AIAgents #LLMEngineering #AgentDevelopment #AIEngineering #BuildingWithAI