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Generative AI
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Generative AI is a branch of artificial intelligence focused on systems that create text, images, code, audio, video, and other new content from learned patterns in data.
In professional knowledge work, it supports drafting, summarization, research synthesis, software assistance, content development, and automation when paired with clear governance and human review.
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Prompt Engineering
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Prompt Engineering is the professional practice of designing instructions for large language models (LLMs) and other Generative AI systems so they produce useful, reliable, and reviewable outputs.
It includes clear task specification, context construction, instruction hierarchy, constraints, examples, structured output formats, iterative refinement, grounding, response evaluation, and reusable prompt templates for tools and AI agents.
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Large Language Models (LLMs)
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Large Language Models (LLMs) are Transformer-based AI systems trained on large text and code corpora to understand, generate, summarize, classify, translate, and reason over language.
They are the foundation for many enterprise chat assistants, coding tools, search experiences, content workflows, and automation systems, especially when combined with Retrieval-Augmented Generation (RAG) and tool use.
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Retrieval-Augmented Generation (RAG)
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Retrieval-Augmented Generation (RAG) combines information retrieval with large language models (LLMs) so responses can be grounded in external documents, knowledge bases, databases, or enterprise content.
RAG is useful for technical documentation, support knowledge, policy search, research synthesis, and internal knowledge-management workflows because it can make AI output more traceable to source material.
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AI Agents / Agentic AI
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AI Agents, or Agentic AI systems, use models, tools, context, memory, and workflow instructions to plan and execute multi-step tasks with human oversight.
In enterprise environments, AI agents can support software maintenance, research, document production, ticket triage, workflow automation, and governed business processes when permissions and validation are handled carefully.
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Multimodal AI
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Multimodal AI systems process and generate information across more than one modality, such as text, images, audio, video, documents, diagrams, and code.
This capability is important for modern content development, accessibility review, visual analysis, image generation, document understanding, and AI-assisted workflows that combine written and visual material.
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OpenAI
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OpenAI is an AI research and product company that develops Generative AI models, APIs, multimodal systems, and agentic development technologies used for conversational AI, content creation, analysis, coding, automation, image generation, and enterprise knowledge work.
Its ecosystem includes ChatGPT, Codex, DALL-E, and the OpenAI API, making it a recognizable platform for modern AI-enabled productivity and software workflows.
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ChatGPT
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ChatGPT is OpenAI's conversational AI product for drafting, analysis, brainstorming, research support, summarization, coding assistance, data work, and multimodal knowledge tasks.
For professional use, ChatGPT supports prompt engineering, document-oriented workflows, content development, AI-assisted research, and structured output generation when paired with verification and source review.
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Codex
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Codex is OpenAI's coding agent for software development, code review, debugging, automation, and repository-aware engineering workflows.
It applies large language models (LLMs) and agentic tooling to help developers and technical contributors work with codebases, scripts, documentation, tests, and change-management tasks.
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DALL-E
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DALL-E is OpenAI's image-generation model family for creating visual assets from natural-language prompts.
It is retained in Skill 4 because it directly supports generative image creation for concept art, illustration drafts, visual ideation, and supporting media assets.
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Adobe Firefly
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Adobe Firefly is Adobe's generative AI creative platform for producing and editing images, video, audio, vectors, text effects, and other media through prompt-based workflows. It belongs in Adobe, AI, graphic design, and content development because it supports professional creative ideation and production inside the Adobe ecosystem. Additional Resources:
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Anthropic
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Anthropic is an AI company that develops Claude models, enterprise AI products, APIs, and agentic coding tools with an emphasis on helpful, reliable, and safety-focused AI systems.
Its products are used for conversational AI, enterprise knowledge work, software development, document analysis, and Generative AI workflows.
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Claude
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Claude is Anthropic's AI assistant and model family for writing, analysis, coding assistance, document review, research, and complex reasoning workflows.
Claude is professionally relevant for prompt engineering, long-context analysis, knowledge work, drafting, review, and governed enterprise AI adoption.
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Claude Code
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Claude Code is Anthropic's agentic coding tool for working with codebases from the terminal, IDE workflows, and developer tooling.
It uses AI agents patterns to help edit files, run commands, explain code, manage Git workflows, and support software maintenance with explicit human control over changes.
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Microsoft Copilot
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Microsoft Copilot is Microsoft's AI assistant experience for work and productivity, including chat, writing, summarization, ideation, and assistance across Microsoft 365 and related Microsoft services. Additional Resources:
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Microsoft Copilot Studio
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Microsoft Copilot Studio is Microsoft's low-code platform for creating, customizing, connecting, and managing AI agents and Copilot experiences across business systems and Microsoft 365 workflows. Additional Resources:
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GitHub Copilot
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GitHub Copilot is an AI coding assistant for the software development lifecycle, including inline suggestions, chat assistance, code explanations, documentation support, and repository-aware development workflows.
It is relevant to large language models (LLMs)-assisted programming, code review, documentation generation, developer productivity, and AI-supported version-control workflows.
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Google Gemini
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Google Gemini is Google's AI assistant and family of multimodal models for text, images, audio, code, research, productivity, and agentic workflows.
Gemini is relevant to multimodal AI, enterprise AI applications through Google Cloud, Workspace productivity, software assistance, and knowledge-work automation.
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Meta AI
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Meta AI is Meta's public AI assistant and generative AI product surface for answering questions, creating images, and supporting consumer and social-platform AI experiences.
It is relevant to Generative AI, image generation, multimodal content creation, and the broader Meta AI research and open-model ecosystem.
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xAI
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xAI is the AI company behind Grok, providing frontier models and APIs for reasoning, coding, voice, image generation, video generation, and real-time experiences connected to X.
The xAI ecosystem is relevant to enterprise and public-facing Generative AI workflows that combine conversational AI, media generation, web-aware answers, and developer APIs.
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Grok
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Grok is xAI's AI assistant for chat, reasoning, coding help, real-time web and X-aware answers, voice interaction, and image/video creation.
It is professionally relevant as a public Generative AI assistant and developer-facing AI platform for research, content work, coding support, and multimodal exploration.
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Grok Imagine
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Grok Imagine is xAI's image and video generation feature for creating visual media from prompts.
It is retained in Skill 4 because it directly creates visual media, unlike broader AI assistant records that are better kept only under AI/ML.
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Cohere
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Cohere is an enterprise AI company that provides models and platforms for language understanding, generation, search, retrieval, agents, embeddings, reranking, and secure workplace AI.
It is relevant to enterprise Retrieval-Augmented Generation (RAG), semantic search, knowledge automation, multilingual AI, and AI systems that need retrieval and governance capabilities.
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Cursor
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Cursor is an AI code editor and coding agent for understanding codebases, planning changes, generating code, fixing bugs, reviewing diffs, and working with developer tools.
It is relevant to AI agents, AI-assisted software development, prompt-driven implementation, and practical coding workflows that combine editor context with model assistance.
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Ollama
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Ollama is a platform for running and managing open models locally or in controlled environments, making it useful for private experimentation, local development, and AI-enabled automation.
It is relevant to large language models (LLMs) workflows, developer testing, privacy-sensitive prototyping, and integrations with tools such as Claude Code, Codex, and GitHub Copilot.
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DeepSeek
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DeepSeek is an AI research company and model platform focused on frontier large language models (LLMs), reasoning, coding, and developer-accessible AI APIs.
It is professionally relevant as part of the open and commercial AI ecosystem for software assistance, experimentation, model evaluation, and OpenAI-compatible API workflows.
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Qwen
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Qwen is Alibaba Cloud's large language and multimodal model family for chat, coding, reasoning, text generation, image understanding, tool use, and agentic applications.
It is relevant to large language models (LLMs), multimodal AI, open-model experimentation, API-based development, and the broader enterprise AI model ecosystem.
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Kimi
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Kimi is Moonshot AI's AI assistant and model ecosystem for long-context work, coding, analysis, slide and document workflows, research, and agentic task execution.
It is relevant to large language models (LLMs) applications in knowledge work, document-heavy analysis, coding support, and multilingual AI workflows.
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NIST AI Risk Management Framework (AI RMF)
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The NIST AI Risk Management Framework helps organizations manage risks from AI systems.
It affects AI documentation through risk mapping, governance records, model and system documentation, transparency, evaluation evidence, monitoring, and responsible AI practices.
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ISO/IEC 42001 - AI Management System
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ISO/IEC 42001 is a management-system standard for artificial intelligence.
It affects AI governance documentation through policies, objectives, risk controls, accountability, lifecycle records, supplier controls, assessments, and continuous improvement.
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