Engineering Case Studies
Post-mortem style technical breakdowns explaining why systems were built, key design trade-offs (Latency vs. Accuracy, Spatial vs. Frequency, Guardrails vs. Retries), bottleneck fixes, and core takeaways.
How Systems Like ChatGPT Manage Long Conversations Efficiently
An engineering analysis of how modern LLM applications manage long-running conversations using context windows, retrieval, summarization, and inference optimizations without exhausting GPU infrastructure.
Large Language Models are fundamentally stateless, yet applications like ChatGPT create the experience of persistent conversation. This case study explores how modern LLM systems combine sliding context windows, retrieval, summarization, persistent memory, KV caching, and efficient inference techniques to balance latency, infrastructure cost, and response quality.