What Happens After You Hit Send? Inside an AI Response
from AI Systems Brief with Krish Hosted by Krish Adavi
AI Systems Brief with Krish — Episode 1 A short prompt can trigger a whole workflow. Follow a hypothetical hiking-boot return request through context gathering, tokens, prefill and decoding, KV caching, scheduling, tool calls and validation. Learn why a faster model does not always mean a faster useful result—and what builders should measure instead. All return-policy details and timing numbers are illustrative, not a live store interaction or measured benchmark. Original explanatory animations accompany Krish's narration. The audio is self-contained. Builder tools: https://a2zai.ai YouTube: https://www.youtube.com/@a2zai-ai Instagram: https://www.instagram.com/a2zai.ai/ Community and other channels: https://a2zai.ai/connect CHAPTERS 00:00 After you hit Send 01:36 The model and the application 03:12 Context, tokens and prefill 05:52 How the answer is generated 07:30 KV caching 09:04 Scheduling and the clocks 10:43 When the assistant acts 12:04 The ten-second example 13:39 Practical builder takeaways 15:15 The whole journey SOURCES https://developer.nvidia.com/blog/mastering-llm-techniques-inference-optimization https://huggingface.co/docs/transformers/main/kv_cache https://huggingface.co/docs/transformers/v5.14.0/continuous_batching_architecture https://docs.nvidia.com/nim/benchmarking/llm/metrics https://www.anthropic.com/engineering/building-effective-agents #a2zai #AISystems #LLM #AIEngineering
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