#ai-reference

200 agentic AI terms — agents, MCP, memory, planning, evaluation, governance. Examples, source links, cross-references. The reference glossary.

120 MCP terms — server, transport, primitive, sampling, prompt, tool, resource, agent loop, governance. The plain-language MCP reference guide.

GEO, AEO, RAG, CRAG, MoE, MCP, ICL, CoT, ReAct, RLHF, DPO, ORPO — 250+ AI marketing acronyms decoded with examples and source citations. Definitive reference.

120 terms across vector search, embeddings, hybrid retrieval, reranking, BM25 fusion, and ANN algorithms. With formulas, code samples, and benchmark references.

Fifty prompt patterns by task type — extraction, transformation, classification, reasoning, agent loops. With model-specific notes and reusable templates.

100 AI governance terms — EU AI Act, NIST AI RMF, ISO 42001, OECD, US state rules. Practical glossary for legal, compliance, and risk teams.

ReAct, Reflexion, plan-execute, multi-agent debate, swarm, hierarchy, blackboard, graph-orchestrated patterns. Reference architectures + trade-offs.

Eighty AI eval metrics — quality (BLEU, ROUGE, BERTScore), agentic (success rate, tool accuracy), safety, fairness, RAG (faithfulness). Defined.

Tokens, prefill, decode, KV cache, prefix cache, batch tier, reserved capacity, context-window discount — every LLM billing term, defined.

Comprehensive comparison of AI model context windows in 2026. From GPT-5.4 and Claude Opus 4.6 at 1M tokens to Llama 4 Scout at 10M. Full reference table.