LLMOps & Performance

Running AI in production — deployment, scaling, latency optimization, cost management, and operational best practices.

Confusion matrix evaluation pipeline connecting scikit-learn, TorchMetrics, and Weights and Biases for model debugging
MAX guide 11 min

Confusion Matrices: scikit-learn, TorchMetrics & W&B (2026)

Specify, build, and validate confusion matrix pipelines with scikit-learn 1.8, TorchMetrics 1.9, and Weights & Biases …

Diagnostic dashboard showing precision recall and F1 score evaluation across classification experiments
MAX guide 11 min

How to Calculate and Tune Precision, Recall, and F1 Score with scikit-learn and TorchMetrics in 2026

Specify precision, recall, and F1 score evaluation in scikit-learn 1.8 and TorchMetrics 1.9. A framework to prevent …

Diagnostic dashboard comparing fairness metrics across protected groups with pass-fail indicators and bias detection alerts
MAX guide 12 min

How to Audit ML Models for Bias Using AI Fairness 360, Fairlearn, and What-If Tool in 2026

Audit ML models for bias with AI Fairness 360, Fairlearn, and What-If Tool. Specification framework for fairness …

Layered safety evaluation architecture with classifier gates, taxonomy contracts, and adversarial test harness
MAX guide 13 min

AI Safety Evaluation: Llama Guard, Perspective API, promptfoo 2026

Production AI safety pipeline with Llama Guard 4, ShieldGemma, and promptfoo. Covers taxonomy design, model evaluation, …

Evaluation dashboard displaying metric layers with test results and production trace visualization
MAX guide 12 min

How to Evaluate LLMs for Your Use Case with DeepEval, Langfuse, and Custom Benchmarks in 2026

Build an LLM evaluation pipeline with DeepEval, Langfuse, and Promptfoo. Covers metrics selection, production tracing, …

MAX mapping inference optimization concepts onto a backend developer's mental model of cost and scaling
MAX Bridge 10 min

Inference Optimization for Developers: What Transfers and What Breaks

LLM inference breaks your cost model, scaling instincts, and test expectations. Learn what transfers from backend …

Engineer examining a layered detection pipeline with verification checkpoints highlighted on a diagnostic interface
MAX guide 12 min

How to Detect and Reduce LLM Hallucinations with DeepEval, RAGAS, and RAG Grounding in 2026

Build a hallucination detection pipeline with DeepEval, RAGAS, and RAG grounding checks. Step-by-step framework for …

Technical deployment diagram showing three inference engines processing batched requests through GPU memory
MAX guide 12 min

How to Deploy Continuous Batching with vLLM, TensorRT-LLM, and SGLang in 2026

Deploy continuous batching with vLLM, TensorRT-LLM, or SGLang using a parameter-by-parameter framework. Covers engine …

Technical control panel with precision dials adjusting LLM output diversity across sampling parameter ranges
MAX guide 11 min

How to Choose and Configure Temperature, Top-P, and Min-P for Every LLM Use Case in 2026

Configure temperature, top-p, and min-p for code generation, creative writing, and RAG pipelines across OpenAI, …

Technical blueprint showing reward model training pipeline with data flowing from preference pairs through evaluation gates
MAX guide 12 min

How to Train and Evaluate a Reward Model with OpenRLHF, TRL, and RewardBench 2 in 2026

Train a reward model using TRL or OpenRLHF, then evaluate with RewardBench 2. Spec-first guide covering architecture, …

Three-layer red team pipeline diagram with vulnerability scanner, attack orchestrator, and probe detector converging on a
MAX guide 12 min

How to Red Team an LLM with Promptfoo, PyRIT, and Garak in 2026

Build an LLM red teaming pipeline with Promptfoo, PyRIT, and Garak. Map attack surfaces, run multi-turn tests, and score …

Decision flowchart mapping LLM quantization formats to GPU and CPU hardware deployment targets
MAX guide 11 min

How to Quantize and Deploy LLMs with AWQ, GGUF, and vLLM on Any Hardware in 2026

Choose the right LLM quantization format for your hardware. AWQ, GPTQ, and GGUF compared — plus current vLLM and …

Production inference server dashboard showing latency curves and throughput metrics across a GPU cluster
MAX guide 12 min

How to Deploy and Optimize LLM Inference with vLLM, TensorRT-LLM, and SGLang in 2026

Deploy production LLM inference with vLLM, TensorRT-LLM, or SGLang. Covers workload profiling, engine selection, FP8 …

Technical blueprint showing compute budget allocation curves splitting between model size and training token count
MAX guide 11 min

How to Apply Scaling Laws and Chinchilla-Optimal Ratios to LLM Training Decisions in 2026

Apply scaling laws and Chinchilla-optimal ratios to real LLM training decisions. Compute budgeting, model sizing, and …

Technical diagram showing the four stages of an RLHF training pipeline with reward model and policy optimization loops
MAX guide 12 min

How to Train a Language Model with RLHF Using OpenRLHF and TRL in 2026

Decompose, specify, and validate a full RLHF training pipeline with OpenRLHF and TRL in 2026. Covers SFT, reward …

Distributed GPU cluster diagram showing tensor and pipeline parallelism layers during language model pre-training
MAX guide 13 min

How to Pre-Train a Language Model with Megatron-LM, DeepSpeed, and NeMo in 2026

Pre-train a language model using Megatron-LM, DeepSpeed, and Megatron Bridge in 2026. Specification-first guide to …

Architectural diagram showing a four-layer fine-tuning specification framework from dataset preparation through model
MAX guide 12 min

How to Fine-Tune an Open-Source LLM with Hugging Face PEFT, Unsloth, and Axolotl in 2026

Fine-tune open-source LLMs with PEFT, Unsloth, and Axolotl using a specification-first framework. Dataset prep, LoRA …

Specification blueprint showing embedding pipeline layers from training data pairs through vector index to search results
MAX guide 12 min

How to Fine-Tune and Deploy Sentence Transformers for Semantic Search and Clustering in 2026

Fine-tune Sentence Transformers v5.3 for semantic search and clustering. Covers MultipleNegativesRankingLoss, Matryoshka …

Multi-vector retrieval pipeline architecture showing ColBERT late interaction between query and document token embeddings
MAX guide 12 min

How to Build a Multi-Vector Retrieval Pipeline with RAGatouille, ColBERTv2, and Qdrant in 2026

Build a production multi-vector retrieval pipeline with ColBERTv2, RAGatouille, and Qdrant. Specification-first …

Technical blueprint showing three interconnected vector index architectures with benchmark performance curves
MAX guide 12 min

How to Build and Benchmark a Vector Index with FAISS, ScaNN, and DiskANN in 2026

Build and benchmark vector indexes with FAISS, ScaNN, and DiskANN. Choose index types by dataset size, tune parameters …

Architecture blueprints showing parallel encoder and decoder pathways with structured data flowing between them
MAX guide 11 min

When to Choose Encoder-Decoder Over Decoder-Only: T5, BART, and Whisper Use Cases in 2026

Learn when encoder-decoder models like T5, BART, and Whisper outperform decoder-only alternatives. A spec framework for …

Engineer examining a vector search pipeline blueprint with index nodes and distance metric annotations on a diagnostic screen
MAX guide 11 min

Similarity Search Pipeline: FAISS, HNSWlib, ScaNN (2026)

Select between FAISS, HNSWlib, and ScaNN for production vector search. Specification-first approach covering index …

Architectural blueprint of attention matrix computation showing QKV projection layers and optimization pathways
MAX guide 10 min

Implementing Attention from Scratch: PyTorch, FlashAttention, and Grouped-Query Optimization

Spec your attention implementation before writing code. Learn to decompose QKV projections, configure FlashAttention …

Blueprint diagram showing three tokenizer library pathways converging into a unified vocabulary specification
MAX guide 12 min

How to Train and Choose a Custom Tokenizer with tiktoken, SentencePiece, and HF Tokenizers in 2026

Learn how to choose, train, and validate a custom tokenizer using tiktoken, SentencePiece, and HF Tokenizers with a …

Specification blueprint overlay on a transformer model architecture diagram with labeled attention heads and data flow arrows
MAX guide 11 min

How to Build and Fine-Tune Transformer Models with Hugging Face and PyTorch in 2026

Build and fine-tune transformer models the specification-first way. PyTorch 2.10, Hugging Face Transformers v5, and the …

Technical blueprint showing a decoder-only transformer pipeline from token embedding through causal masked attention to
MAX guide 13 min

How to Build a Decoder-Only Transformer and Select the Right Pretrained Model in 2026

Build a decoder-only transformer with correct causal masking in PyTorch, then pick between GPT-5, LLaMA 4, and DeepSeek …

Blueprint schematic of a semantic search pipeline with embedding vectors flowing through indexing and retrieval stages
MAX guide 12 min

Embedding Models: Voyage 4 vs NV-Embed-v2 vs BGE-M3 2026

Choose between Voyage 4, NV-Embed-v2, and BGE-M3. Includes Matryoshka embeddings and cost optimization strategies for …

Specification blueprint overlaid with attention weight heatmaps flowing between token sequences
MAX guide 11 min

How to Implement Multi-Head Attention in PyTorch and Visualize Attention Patterns

Specify multi-head attention for AI-assisted PyTorch builds. Decompose QKV projections, constrain SDPA kernels, and …

Architectural blueprint of a transformer model with labeled attention layers and data flow arrows on a dark grid
MAX guide 12 min

How to Build a Transformer from Scratch Using PyTorch and Hugging Face

Specify a transformer from scratch in PyTorch and Hugging Face. Decompose attention, embeddings, and training loops into …