AI Tools

Practical AI for builders — prompt engineering, agent orchestration, generative media, and deployment workflows. MAX focuses on what works in production.

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 …