Tag: #llm
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 209 posts
Forward Deployed Engineer Career Guide: The fastest growing problem-solving engineer job in the AI era ♪ Listenable
The actual role of a Forward Deployed Engineer (FDE), differences from general software engineers/solution architects, required competencies, career growth path, and 90-day preparation roadmap are summarized based on the
2026-03-07 · 7 min read #ai-platform#forward-deployed-engineer#career#llm#enterprise-aivLLM PagedAttention Production Serving Optimization and Inference Engine Comparison Guide ♪ Listenable
A comprehensive LLM serving guide covering vLLM PagedAttention algorithm, production deployment, performance tuning, SGLang/TensorRT-LLM comparison, and Kubernetes integration.
2026-03-06 · 22 min read #llm#vllm#paged-attention#model-serving#2026-03Complete LLM Quantization Comparison: GPTQ, AWQ, GGUF Practical Application Guide ♪ Listenable
From the core principles of LLM quantization to comparative analysis of GPTQ, AWQ, GGUF, and BitsAndBytes techniques, covering practical application in vLLM and llama.cpp environments and quality-performance trade-offs.
2026-03-06 · 14 min read #llm#quantization#gptq#awq#ggufLLM Multimodal Vision-Language Model Serving and Optimization Practical Guide ♪ Listenable
A practical guide to serving and optimizing multimodal vision-language models in production.
2026-03-05 · 24 min read #llm#multimodal#vlm#vllm#2026-03LLM Speculative Decoding Serving Optimization Playbook
LLM Speculative Decoding Serving Optimization Playbook - a hands-on adoption guide as of 2026
2026-03-04 · 14 min read #llm#speculative-decoding#2026-03LLM QLoRA Fine-Tuning Operations Guide: Cost, Quality, and Deployment
LLM QLoRA Fine-Tuning Operations Guide: A comprehensive practical document covering cost, quality, and deployment, including Why/How/When, comparison tables, troubleshooting, hands-on code, and quizzes.
2026-03-04 · 8 min read #llm#practical-guide#productionLLM Serving: Speculative Decoding Production Benchmark 2026
LLM Serving: Speculative Decoding Production Benchmark 2026 - A practical guide covering Why, How, When, comparison tables, troubleshooting, code examples, and quizzes.
2026-03-04 · 14 min read #llm#2026-03LLM RAG Pipeline: Chunking Strategies and Embedding Optimization in Practice 2026 ♪ Listenable
A practical guide covering the core of LLM RAG pipelines: chunking strategies and embedding optimization. From comparing fixed-size, semantic, and recursive chunking to embedding model selection, vector DB indexing, and
2026-03-04 · 19 min read #llm#2026-03Complete LLM Quantization Comparison — GPTQ vs AWQ vs GGUF ♪ Listenable
A comprehensive guide to LLM Quantization — from quantization fundamentals to comparing GPTQ, AWQ, and GGUF methods, vLLM/llama.cpp integration, and practical benchmarks.
2026-03-03 · 6 min read #llm#quantization#gptq#awq#ggufThe Complete vLLM Guide — From PagedAttention to Production Optimization
Covering everything about LLM inference optimization — from vLLM core PagedAttention mechanism to Continuous Batching, Tensor/Pipeline Parallelism, and Prefix Caching.
2026-03-03 · 9 min read #llm#vllm#inference#paged-attention#model-servingComplete Guide to LLM Function Calling: From Tool Use Patterns to Production Design
A deep dive into the Function Calling (Tool Use) mechanism of LLMs. Covers implementation methods across OpenAI, Anthropic, and open-source models, along with error handling, parallel invocation, and production design pa
2026-03-03 · 8 min read #llm#function-calling#tool-use#openai#ai-agentLLM Structured Output Practical Guide — JSON Mode, Tool Use, Pydantic Schema Validation ♪ Listenable
Compare Structured Output approaches across OpenAI, Anthropic, and Google, covering Pydantic schema validation to production pipeline construction with practical code examples.
2026-03-03 · 22 min read #llm#structured-output#json-mode#openai#anthropicComplete Guide to LLM Context Window Extension: From RoPE, ALiBi, and YaRN to Ring Attention
An in-depth analysis of techniques for extending LLM context windows from 512 to 2M tokens. Covers the mathematical principles of RoPE through NTK-aware scaling, YaRN, and Ring Attention with practical code examples.
2026-03-03 · 9 min read #llm#context-window#rope#yarn#positional-encodingBuild Your Own GPT — Training a Language Model from Scratch with nanoGPT
Train a GPT language model from scratch using Andrej Karpathy's nanoGPT. A complete dissection of the Transformer architecture — tokenizers, Self-Attention, training loops — all with code.
2026-03-03 · 7 min read #ai#llm#gpt#nanogpt#transformerBuilding Scalable LLM Serving Pipelines with Ray Serve
From core concepts of ML/LLM model serving with Ray Serve to multi-model pipelines, autoscaling, batch inference, and production deployment — all with code examples.
2026-03-03 · 6 min read #ai-platform#ray-serve#model-serving#llm#mlopsPractical LLM Fine-Tuning — Building Your Own Model with LoRA, QLoRA, and PEFT
A practical guide to LLM fine-tuning. From the mathematical principles of LoRA to training large models on consumer GPUs with QLoRA, and leveraging the PEFT library — all with detailed code examples.
2026-03-02 · 7 min read #llm#fine-tuning#lora#qlora#peftAccelerating LLM Inference 2-3x with Speculative Decoding: From Theory to Production
A deep dive into the mathematical foundations of Speculative Decoding, the Draft-Verify pipeline, acceptance probability analysis, practical implementation in vLLM/TensorRT-LLM, and Apple's Mirror Speculative Decoding.
2026-03-02 · 8 min read #llm#speculative-decoding#inference#optimization#vllmBuilding a RAG Chatbot — Create Your Own Document QA Bot with LangChain + ChromaDB + OpenAI
A hands-on guide to building a PDF document-based RAG chatbot from scratch using LangChain, ChromaDB, and OpenAI. Covers document loading, vector storage, prompt design, and a Streamlit UI.
2026-03-02 · 9 min read #rag#langchain#chromadb#openai#chatbotLangGraph Agent Workflow Practical Guide: From Multi-Agent Orchestration to Production Deployment
Build stateful AI agent workflows with LangGraph. Covers StateGraph, conditional routing, multi-agent orchestration, Human-in-the-Loop, and LangGraph Platform deployment — all with production-ready code.
2026-03-02 · 6 min read #langgraph#langchain#ai-agent#workflow#multi-agentProduction LLM Application Architecture Design Guide ♪ Listenable
Analyze the core architecture layers of production LLM applications and organize Gateway, Guardrails, Caching, and Observability components based on official documentation.
2026-03-01 · 21 min read #llm#architecture#production#ai#guardrails