LLM Inference Engineering Maps Modern Serving
This open-source learning guide from Amit Shekhar teaches LLM inference step by step, covering KV caches, PagedAttention, continuous batching, speculative decoding, vLLM, SGLang, quantization, routing, and GPU hardware.
Inference is becoming a core software-engineering discipline because latency, throughput, and GPU costs increasingly determine whether AI products work in production.
- –Bridges model concepts with practical serving systems and hardware fundamentals
- –Explains the optimization techniques behind higher throughput and lower memory use
- –Covers both hosted engines such as vLLM and SGLang and local formats such as GGUF
- –Gives application developers a useful path toward production-grade AI infrastructure skills
- –Best treated as a structured curriculum and reference library, not a turnkey inference platform
DISCOVERED
1h ago
2026-08-19
PUBLISHED
2h ago
2026-08-19
RELEVANCE
AUTHOR
techNmak