Terminology
2185 terms, tools, patterns and metrics an architect is expected to use precisely. Each one gets a short explanation of what it is, and — where it matters — what it is commonly confused with. Search filters as you type; the column headers sort.
All areas2185
Architecture Fundamentals77
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Data Architecture110
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Observability70
Performance & Capacity Engineering72
Security Architecture81
Cost Architecture & FinOps66
Business Architecture67
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AI-Era Architecture69
Software Architecture & Engineering71
Architecture Patterns71
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The Architect's Meta-Skills61
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Streaming & Real-Time Data69
Data Governance & Semantics69
Frontend & Experience Architecture66
Edge, Mobile & IoT68
Regulatory & Data Protection Architecture65
Assurance, Audit & Model Risk64
23 terms shown.
| Term | Kind | Topic | What it is |
|---|---|---|---|
| Agent Handoff | pattern | Multi-Agent Systems | The transfer of a task and its context from one specialised agent to another, and the point at which multi-agent systems most often lose information. |
| Agent Tool Authorisation | pattern | Tool Calling | Enforcing that a tool invoked by a model executes with the requesting user's permissions rather than the application's, and that consequential actions require confirmation. |
| Agent Transcript Compaction Loop History Summarisation, Working Memory Compaction | pattern | Agent Architectures | Replacing the resolved middle of a long agent loop with a short summary while preserving the original goal and constraints verbatim, so token cost stops growing quadratically and late steps still follow early … |
| AI Gateway | pattern | AI-Era Architecture | A shared proxy in front of model providers that centralises routing, keys, quotas, caching, logging and safety policy. |
| AI Gateway Pattern LLM Proxy, Model Router | pattern | AI Gateways | A single control point through which all model calls pass, providing routing, cost control, caching, logging, guardrails and provider abstraction. |
| Chunked Prefill Prefill Splitting, Interleaved Prefill, Piecewise Prompt Processing | pattern | AI Cost Management | Breaking a long prompt's prefill into pieces interleaved with other sequences' decode steps, so that one enormous request cannot stall every in-flight interactive response. |
| Contextual Retrieval Contextual Chunk Prefixing, Contextual Embeddings | pattern | Chunking & Retrieval | Prepending a short generated description of where a chunk sits in its document before embedding it, so that a passage full of pronouns and bare figures still matches the query that should find it. |
| Filtered Vector Search Predicate-Constrained ANN, Metadata Filtering in ANN | pattern | Vector Databases | Combining a metadata predicate with approximate nearest-neighbour search - where the predicate's selectivity, not the corpus size, decides whether results are correct or latency collapses. |
| Guardrails | pattern | Guardrails | Deterministic checks applied to model inputs and outputs, enforcing constraints that the model itself cannot be relied upon to respect. |
| Human in the Loop HITL | pattern | AI-Era Architecture | Requiring human review or approval at a defined point in an automated flow, chosen by the reversibility and cost of the action. |
| Human-in-the-Loop Design | pattern | Human in the Loop | Placing human review at the points where model error is consequential, designed so the review is genuinely effective rather than nominal. |
| Hybrid Retrieval Dense + Sparse Retrieval, BM25 + Vector | pattern | RAG Architecture | Running lexical keyword search and dense vector search together and fusing the results, because each fails where the other succeeds. |
| Model Cascade Tiered Inference, Escalation Ladder | pattern | Model Selection | A cheap fast model handling the clear majority of cases with escalation to a larger model or a human for the uncertain ones - usually a large cost reduction with no quality loss, because the expensive path run… |
| Model Router | pattern | AI-Era Architecture | Directing each request to a model chosen by the task's difficulty, cost and latency budget, rather than sending everything to the largest model available. |
| Model Routing | pattern | Model Selection | Directing each request to the cheapest model capable of handling it, rather than sending all traffic to the most capable one. |
| Output Validation Layer | pattern | Guardrails | A deterministic check applied to model output before it is used, treating the model as an untrusted component. |
| Reranking Cross-Encoder Reranking | pattern | Reranking | Retrieving a wide candidate set cheaply, then reordering it with a more expensive model that scores each candidate against the query directly. |
| Retrieval Pipeline Stages | pattern | RAG Architecture | The stages that turn a user question into grounded context — query processing, retrieval, reranking and assembly — each independently tunable. |
| Retrieval-Augmented Generation RAG | pattern | AI-Era Architecture | Retrieving relevant documents at query time and putting them in the model's context, so answers are grounded in your data rather than in training data. |
| Semantic Cache | pattern | AI-Era Architecture | Caching model responses keyed by the meaning of the request rather than by its exact text, so near-duplicate questions are served without a model call. |
| Tool Calling Function Calling | pattern | AI-Era Architecture | Giving a model a set of typed function definitions it can request to invoke, with the application executing the call and returning the result. |
| Tool Result Budget Tool Output Capping, Result Truncation Contract | pattern | Tool Calling | A hard cap on the tokens any single tool may return into the model's context, with pagination and summarisation behind it, so that one unlucky query cannot fill the window and end the run. |
| Two-Stage Retrieval | pattern | Reranking | Retrieving a broad candidate set cheaply and then reordering it with an expensive, more accurate model. |
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