Search the practice set
126 questions, 454 terms and 400 topics in 20 areas.
41 results for “AI Gateways”
AI Gateway
A shared proxy in front of model providers that centralises routing, keys, quotas, caching, logging and safety policy.
Context Window
The maximum number of tokens a model can attend to in one request, holding the system prompt, history, retrieved context, tools and the answer.
Embedding
A dense numeric vector representing a piece of content, positioned so that semantically similar content sits nearby.
Guardrail
A deterministic check applied to a model's input or output, enforcing rules that cannot be left to the model itself.
Human in the Loop
Requiring human review or approval at a defined point in an automated flow, chosen by the reversibility and cost of the action.
LLM Evaluation
A repeatable measurement of whether an AI system's outputs are good enough, on cases that reflect the actual task.
Model Context Protocol
An open protocol that standardises how AI applications connect to external tools, data sources and prompts.
Model Router
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.
Prompt Injection
An attack in which text from an untrusted source is interpreted by the model as instructions rather than as data.
Prompt Registry
A versioned store of production prompts with their model bindings, parameters and evaluation results, so a prompt change is a reviewable, traceable, reversible deployment.
Prompt Versioning
Treating prompts as versioned, reviewed, tested artefacts rather than as strings edited in place.
Retrieval-Augmented Generation
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
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
Giving a model a set of typed function definitions it can request to invoke, with the application executing the call and returning the result.
Uber's Domain-Oriented Microservice Architecture
After growing to roughly 2,200 microservices, Uber grouped them into domains behind gateways with strict dependency layering, to recover the comprehensibility that fine-grained de…
Vector Database
A store optimised for approximate nearest-neighbour search over high-dimensional embeddings.
You are asked to give an internal AI agent access to the customer database, the ticketing system and outbound email so it can resolve support tickets. What is your response?
What the interviewer is testing Whether you recognise a specific and well documented security pattern, and whether you can propose a workable design instead of
A client wants an assistant that answers questions from 50,000 internal documents which change weekly. RAG or fine-tuning? What actually determines the quality?
What the interviewer is testing Whether you understand what each technique actually does, and whether you know that RAG quality is a retrieval problem. Why RAG
An LLM feature that worked last week now gives worse answers. Nothing was deployed. How do you find out what changed, and what should have been in place?
What the interviewer is testing Whether you treat an AI feature as a system with configuration and dependencies, or as a black box that mysteriously drifts. Wha
AI Gateways
Centralised routing, keys, quotas, caching, logging and safety policy.
AI Cost Management
Token accounting, routing, caching and the context-window budget.
AI Observability
Logging prompts, versions, retrieved context and cost per request.
AI-Era Architecture
General material on architecting systems that include models.
API Gateways
The single entry point, and the business logic that must stay out of it.
Agent Architectures
Loops, planning, memory and the boundaries an agent must not cross.
Chunking & Retrieval
Structure-aware splitting, hybrid search and why chunking dominates quality.
Embeddings
Dense representations, model coupling and the migration they imply.
Guardrails
Deterministic checks on input and output that fail closed.
Human in the Loop
Gating by reversibility and blast radius, and avoiding approval fatigue.
LLM Application Architecture
The shape of a production system with a model in the request path.
LLM Evaluation
Held-out sets, rubric judging, CI gates and production sampling.
ML Platform
Feature stores, training pipelines, registries and deployment.
Model Selection
Capability, latency, cost and the evaluation that decides between them.
Multi-Agent Systems
Coordination, hand-off and whether more agents actually help.
Prompt & Version Management
Prompts as reviewed, versioned, evaluated production configuration.
Prompt Injection Defence
Breaking the private-data, untrusted-input, outbound-channel combination.
RAG Architecture
Retrieval, grounding, citation and the permissions RAG can enforce.
Reranking
Cross-encoders improving precision more than a bigger embedding model.
Tool Calling
Typed tool interfaces, narrow parameters and per-tool authorisation.
Vector Databases
Approximate nearest-neighbour search, filtering and re-indexing.