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Agentic AI
Autonomous AI systems that plan, reason, and act across tools with minimal human input.
Clear explanations of AI, automation, and agentic terms—concise, practical, and built for curious builders.
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These are the concepts most teams encounter first when exploring AI agents, automation, and AshnaAI.
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Autonomous AI systems that plan, reason, and act across tools with minimal human input.
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Fetching relevant documents before generating an answer for better accuracy.
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Software entities that break goals into tasks and execute them using models, data, and APIs.
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Neural networks trained on vast text corpora to understand and generate language.
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Designing instructions and examples that steer model behavior reliably.
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Building AI applications without traditional programming skills.
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Showing 30 terms
Autonomous AI systems that plan, reason, and act across tools with minimal human input.
Software entities that break goals into tasks and execute them using models, data, and APIs.
Computer systems designed to perform tasks that typically require human intelligence.
Enriching models with external context, tools, or data for more accurate outputs.
A prompting technique where models reason step-by-step before giving a final answer.
Splitting large documents into smaller pieces for efficient retrieval and RAG.
A signal of how certain a model is about a prediction or classification.
The maximum amount of text a model can process in a single request.
Systems that interact through natural language across chat, voice, and messaging.
AI that creates new text, images, code, or audio from learned patterns.
A family of transformer-based language models used for text generation and agents.
Anchoring model outputs to trusted sources to reduce hallucinations.
Policies and controls that keep AI outputs safe, compliant, and on-brand.
When a model produces confident but incorrect or unsupported information.
Keeping people involved in approvals, corrections, or escalations.
Combining keyword and semantic search for better retrieval quality.
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