AI
Context Window Management in Agentic Systems
Context management is the key bottleneck in agentic systems. Summarization, retrieval, memory separation, and structured planning keep prompts lean, costs low, and agents focused.
AI
Context management is the key bottleneck in agentic systems. Summarization, retrieval, memory separation, and structured planning keep prompts lean, costs low, and agents focused.
AI
Prompt processing in LLMs is compute-heavy, as every token passes through billions of parameters. Even with big GPUs it can feel slow, but quantization, optimized backends, and future NPU offloading promise big speedups.