
Build a Multimodal RAG Pipeline with ColPali, Jina v4, RAGFlow in 2026
Multimodal RAG turns PDF pages, charts, and screenshots into searchable knowledge. Spec a 2026 stack with ColPali, Jina …

How to Build a Document Parsing Pipeline with LlamaParse, Unstructured, and Docling in 2026
Build a document parsing pipeline that routes PDFs to LlamaParse, Unstructured, or Docling by complexity. A …

Metadata Filtering in Qdrant, Weaviate, Milvus & Pinecone (2026)
Specification-first guide to metadata filtering in Qdrant, Weaviate, Milvus, and Pinecone — tenancy, date filters, and …

How to Build a GraphRAG Pipeline with Neo4j and LightRAG in 2026
Build a knowledge-graph RAG pipeline with Microsoft GraphRAG, Neo4j vector indexes, and LightRAG. Decompose components, …

Long-Context vs RAG vs Hybrid: A 2026 Decision Framework
Long-context, RAG, or hybrid? A 2026 spec-driven framework for choosing between Gemini 3.1 Pro 1M, Claude Sonnet 4.6, …

RAG Evaluation Harness with RAGAS, DeepEval, and TruLens in 2026
Build a production RAG evaluation harness with RAGAS 0.4, DeepEval 3.9, and TruLens 2.8. Spec the metrics, gate CI, …

RAG Hallucination Detection with Ragas, TruLens & Guardrails (2026)
Wire Ragas, TruLens, and Guardrails AI into your RAG pipeline to catch hallucinations before users see them. A …

Build a Hybrid Search Pipeline: BM25, SPLADE-v3 + RRF in 2026
Vector search still misses rare terms. Here's how to architect a hybrid retrieval pipeline with BM25, SPLADE-v3, and …

Build a Contextual Retrieval Pipeline: Anthropic + Voyage + ColBERT
Contextual retrieval cuts RAG retrieval failures by up to 67%. Here is the pipeline spec for 2026 — Anthropic recipe, …

How to Build Agentic RAG with LangGraph, LlamaIndex & Haystack in 2026
Production agentic RAG in 2026 means hybrid search, cross-encoder rerank, and bounded loops. Spec the pipeline before …

Query Transformation Pipeline: HyDE & LangChain v1 in 2026
Build a query transformation pipeline in 2026 with HyDE, MultiQueryRetriever, and LangChain v1. Decide when each …

HyDE vs Multi-Query vs Step-Back: Choosing RAG Query Transforms
Pick the right RAG query transformation. When HyDE beats multi-query, step-back outperforms decomposition, and routing …

Add Reranking to Your RAG Pipeline: Cohere, Voyage, Zerank-2 in 2026
Add a reranker to your RAG pipeline in 2026. Compare Cohere Rerank 4 Pro, Voyage Rerank-2.5, Zerank-2, and self-hosted …

Production RAG with LangChain, Qdrant & Cohere Rerank in 2026
Build a production RAG pipeline in 2026 with LangChain, Qdrant hybrid retrieval, Cohere Rerank 4, and Ragas eval. Specs, …

How to Build a Hybrid Search Pipeline with Weaviate, Qdrant, and SPLADE in 2026
Build a hybrid search pipeline by decomposing it into sparse, dense, and fusion specs. Covers Weaviate, Qdrant, and …

Multimodal Pipeline 2026: LLaVA, Llama 3.2 Vision & Gemini 3.1 Pro
Architect a multimodal AI pipeline in 2026. Compare Gemini 3.1 Pro, LLaVA-OneVision, and Llama 3.2 Vision by encoder, …

How to Build, Fine-Tune, and Deploy Diffusion Models with Diffusers, ComfyUI, and LoRA in 2026
Build, fine-tune, and deploy diffusion models in 2026 — spec the four surfaces that separate stable Flux.2 and SD 3.5 …

How to Build and Fine-Tune State Space Models with Mamba-3, Jamba, and Nemotron-H in 2026
Build and fine-tune state space models with Mamba-3, Jamba, and Nemotron-H. Architecture mapping, install contracts, and …

How to Fine-Tune SigLIP 2, DINOv2, and ViT Backbones with Hugging Face and PyTorch in 2026
Pick the right Vision Transformer backbone for 2026. Spec-first guide to fine-tuning SigLIP 2, DINOv2, and ViT with …

How to Run and Fine-Tune Open-Weight MoE Models with DeepSeek-V3, Mixtral, and Llama 4 in 2026
Deploy and fine-tune open-weight MoE models like DeepSeek-V3, Mixtral 8x22B, and Llama 4. Hardware mapping, expert …

How to Build a Graph Neural Network with PyTorch Geometric and DGL in 2026
Specify graph neural networks for AI-assisted development. Covers PyTorch Geometric and DGL decomposition, data …

How to Build a VAE in PyTorch and Apply It to Anomaly Detection and Data Augmentation in 2026
Build a variational autoencoder in PyTorch 2.11 the specification-first way. Decompose, specify, and validate your VAE …

How to Build a GAN with PyTorch and Apply It to Super-Resolution and Synthetic Data in 2026
Build a GAN in PyTorch by decomposing the architecture into generator, discriminator, and training loop specs. Covers …

How to Build an LSTM in PyTorch and Where RNNs Still Outperform Transformers in 2026
Learn when LSTMs beat transformers in 2026 — edge deployment, anomaly detection, time series — and how to specify an …

PyTorch CNN: EfficientNetV2 vs ResNet vs ConvNeXt (2026)
Evaluate EfficientNetV2, ResNet, and ConvNeXt. Get a clear decision framework to choose the right PyTorch model for your …

How to Build a Neural Network Language Model from Scratch with PyTorch in 2026
Decompose a neural network language model into four specification layers for AI-assisted development. Covers …

How to Benchmark LLMs with lm-evaluation-harness, HELM, and OpenCompass in 2026
Choose the right LLM evaluation harness — lm-evaluation-harness, HELM, or OpenCompass — with a spec-first workflow for …

How to Detect and Prevent Benchmark Contamination with CoDeC, CCV, and LiveBench in 2026
Detect benchmark contamination in LLMs using CoDeC, CCV, and LiveBench. A step-by-step workflow for auditing evaluations …

How to Design and Run Rigorous Ablation Experiments with ABLATOR, W&B Sweeps, and PyTorch in 2026
Design rigorous ablation experiments with ABLATOR, W&B Sweeps, and PyTorch 2.11. Specify, isolate, and prove which of …

How to Run MMLU Evaluation and Interpret Benchmark Scores for Model Selection in 2026
Run MMLU and MMLU-Pro evaluations correctly, avoid common configuration mistakes, and interpret benchmark scores to …