lAItest / AI field guide · edition 2026-09-26
Know the language. Build with clarity.
Plain-English definitions for the concepts, patterns, protocols, and tools behind modern AI work.
414 defined terms · 16 topic areas · 50 essentials
Retrieval & knowledge terms
31 matching terms.
- Embedding Concept · Retrieval & knowledge
A learned vector representation used for similarity and other downstream tasks.
- Grounding Concept · Retrieval & knowledge
Tie generated claims or actions to relevant evidence and observations.
- Hybrid search Concept · Retrieval & knowledge
Combine complementary retrieval methods, commonly lexical and dense vector search.
- RAG Pattern · Retrieval & knowledge
Retrieval-augmented generation: fetch external evidence and use it to support a generated response.
- Reranker Concept · Retrieval & knowledge
A component that re-scores an initial candidate set for relevance.
- Agentic RAG Pattern · Retrieval & knowledge
Let an agent decide what to retrieve, whether evidence is sufficient, and when to search again.
- ANN Concept · Retrieval & knowledge
Approximate nearest-neighbor search: trade some exactness for efficient similarity lookup.
- BM25 Concept · Retrieval & knowledge
A lexical relevance-ranking method based on term occurrence and document statistics.
- Chunk overlap Concept · Retrieval & knowledge
Repeat boundary content across adjacent chunks to preserve local context.
- Chunking Concept · Retrieval & knowledge
Split source material into units for indexing, retrieval, or processing.
- Cross-encoder Concept · Retrieval & knowledge
A model that jointly processes a query and candidate to estimate their relationship.
- Data lineage Concept · Retrieval & knowledge
The chain of transformations and dependencies through which data reached its current state.
- Deletion propagation Concept · Retrieval & knowledge
Ensure removed source content also disappears from indexes, caches, and derived stores as required.
- Dense retrieval Concept · Retrieval & knowledge
Retrieve candidates using dense vector representations.
- Graph engineering Concept · Retrieval & knowledge
An informal umbrella for designing graph-shaped representations, dependencies, or knowledge structures used by AI systems.
- GraphRAG Concept · Retrieval & knowledge
Use graph-derived structure to support retrieval and synthesis; implementations vary.
- HNSW Concept · Retrieval & knowledge
Hierarchical Navigable Small World: a graph-based approximate nearest-neighbor index.
- HyDE Concept · Retrieval & knowledge
Hypothetical Document Embeddings: generate a hypothetical answer document and use its embedding for retrieval.
- Index freshness Concept · Retrieval & knowledge
How well indexed information reflects the current source state.
- Metadata filtering Concept · Retrieval & knowledge
Restrict candidates by structured attributes such as date, tenant, source, or document type.
- Parent-child retrieval Concept · Retrieval & knowledge
Match a smaller passage, then retrieve its larger containing context.
- Permission-aware retrieval Concept · Retrieval & knowledge
Enforce access restrictions when selecting and returning source material.
- Provenance Concept · Retrieval & knowledge
Information about where a fact or artifact originated.
- Query decomposition Concept · Retrieval & knowledge
Split a complex information need into multiple retrievable subquestions.
- Query rewriting Concept · Retrieval & knowledge
Reformulate a request to make retrieval more effective.
- RAG 2.0 Pattern · Retrieval & knowledge
An informal label for an iteration of retrieval-augmented generation that claims improved retrieval, indexing, agent behavior, or evaluation.
- RRF Concept · Retrieval & knowledge
Reciprocal rank fusion: combine ranked result lists using rank-based scores.
- Semantic search Concept · Retrieval & knowledge
Search by represented meaning rather than only literal word overlap.
- Source attribution Concept · Retrieval & knowledge
Associate claims with the source material supporting them.
- Sparse retrieval Concept · Retrieval & knowledge
Retrieve using sparse term or feature representations.
- Vector database Concept · Retrieval & knowledge
A data system designed to store vectors and support similarity retrieval, often with metadata filters.
Browse by topic
- Agents & architecture 23 — Who decides, what executes, and where control lives.
- Goals, specs & plans 23 — Describe the outcome before delegating the implementation.
- Loops, critics & adversaries 33 — Understand how work is challenged, repaired, and stopped.
- Multi-agent coordination 21 — Delegation, ownership, context boundaries, and aggregation.
- Context & memory 29 — What the model sees now, and what persists for later.
- Tools & output contracts 20 — Model proposals become validated, authorized operations.
- Protocols & interoperability 19 — Name the boundary: tools, agents, editors, or interfaces.
- Coding-agent internals 25 — Instructions, skills, hooks, tools, and durable artifacts.
- Retrieval & knowledge 31 — Find evidence, rank it, and preserve source boundaries.
- Evals & observability 29 — Measure outcomes and inspect the execution path.
- Inference & performance 28 — Latency, throughput, compute, and memory are different constraints.
- Models, reasoning & training 36 — Separate weight changes from context and inference-time work.
- Security & reliability 27 — Make privileges explicit and side effects recoverable.
- Generative UI & voice 18 — The interaction layer has its own contracts and timing.
- Generative & physical AI 8 — Broader model families beyond text-based assistants.
- Tools & ecosystem 44 — Recognize the role before choosing the dependency.