How we optimized a local Llama 3 agent: From 15s latency and 68% accuracy to 4s and 100% (Full E2E Code & Guide)

As you add business logic, policies, and API tool schemas, your system prompt grows into a 500-line monster. On local hardware, this leads to: Massive prefill times (noticeable latency before the first token). "Loss in the middle" and hallucinated calculations. High token costs and fragile JSON parsing. We recently adapted the " Agent Decomposition " principles shown in Anthropic's team member (William Steuk) in the last