AI Context Management
Home
🔌

MCP Tutorials

Step-by-step tutorials for building Model Context Protocol servers and clients in production, with full working code.

1 articles
📖

RAG Cookbook

Working RAG patterns with runnable code: hybrid retrieval, reranking, query expansion, and citation grounding.

1 articles
🧩

Library Integrations

Hands-on integration guides for LangChain, LlamaIndex, Pinecone, Weaviate, Qdrant, and the major LLM SDKs.

1 articles
🪟

Context Window Engineering

Practical techniques for managing context windows: chunking, summarization, sliding windows, and prompt caching.

0 articles
🧮

Embeddings & Retrieval

Embedding model selection, vector store setup, similarity search tuning, and retrieval evaluation methodology.

0 articles
🛠️

Tool Use & Function Calling

Building agentic AI features: tool definitions, function-calling patterns, and tool-orchestration loops.

0 articles
View all 8 categories →
All Categories Glossary
Home All Categories Glossary MCP Tutorials RAG Cookbook Library Integrations Context Window Engineering Embeddings & Retrieval Tool Use & Function Calling
  1. Home
  2. /
  3. Glossary
  4. /
  5. AI Alignment
Glossary AI Safety 1 min read

AI Alignment

Also known as: Value Alignment, AI Safety Alignment

The research field focused on ensuring that AI systems' goals, behaviors, and values are compatible with human intentions and societal well-being throughout their operation.

test annotation

Sources & References

1
Core Views on AI Safety: When, Why, What, and How

Anthropic

2
Our Approach to AI Safety

OpenAI

3
NIST AI Risk Management Framework

National Institute of Standards and Technology

Government

Related Terms

Artificial General Intelligence

A hypothetical form of AI that possesses the ability to understand, learn, and apply intelligence across any intellectual task that a human being can, exhibiting flexibility and adaptability across domains.

Hallucination

When an AI model generates information that sounds plausible but is factually incorrect, fabricated, or not supported by its training data or provided context.

Reinforcement Learning from Human Feedback

A training technique that uses human evaluations of AI outputs to train a reward model, which then guides the AI system to produce outputs more aligned with human preferences.

Responsible AI

The practice of designing, developing, deploying, and using AI systems in ways that are ethical, transparent, fair, accountable, and aligned with human rights and societal values.

Previous Adaptive Batch Sizing Controller
Next AI Governance
Back to Glossary
AI
Context Management

Enterprise context management solutions for AI systems. Building the future of intelligent context handling.

Quick Links

  • Home
  • Tutorials
  • Glossary

Contact

  • info@aicontextmanagement.com

Context Management Network

EC
Enterprise Context Management
Governance, compliance & enterprise-grade context architecture
EP
ECM Protocol
Standards, specifications & protocol documentation

© 2026 AI Context Management. All rights reserved.