ki-konzepte Prompting
Chain-of-Thought
Chain-of-Thought (CoT) is a prompting technique that asks the model to spell out its reasoning in intermediate steps — boosting accuracy on multi-step tasks.
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Prompting
Techniken zur Steuerung von Sprachmodellen über Eingabeaufforderungen.
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Constitutional AI
Constitutional AI is a training method developed by Anthropic in which an AI model critiques and revises its own behaviour against an explicit list of principles (a "constitution") — rather than relying solely on human ratings.
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Context Engineering
Context engineering is the discipline of deliberately curating and maintaining everything inside the LLM context window — system prompt, tool definitions, RAG hits, memory, conversation history.
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Few-Shot Prompting
Few-shot prompting is a technique that includes a handful of input/output examples in the prompt so the model picks up the desired format and style.
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Guardrails
Guardrails are protective layers around a language model that inspect inputs and outputs to catch unwanted behaviour — off-topic answers, PII leaks, unsafe actions.
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Indirect Prompt Injection
Indirect prompt injection is an attack that hides malicious instructions inside external content — web pages, documents, emails — that an LLM then processes and unintentionally executes.
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Jailbreak
A jailbreak deliberately bypasses a language model's safety and behaviour rules through cleverly crafted prompts, making the model produce content it would normally refuse.
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Meta-Prompting
Meta-prompting is the technique of having an LLM write or improve a prompt for a task rather than formulating it yourself — the prompt becomes the output.
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Prompt engineering
Prompt engineering is the discipline of steering AI models through carefully crafted input prompts — closer to precise writing than to classic programming.
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Prompt Injection
Prompt injection is an attack that hides instructions inside an LLM's input data to make the model ignore or subvert its original instructions.
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Prompt Leaking
Prompt leaking is an attack that tricks an LLM into revealing its hidden system prompt or other confidential context contents — a special case of prompt injection.
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Prompt Template
A prompt template is a reusable prompt skeleton with placeholders that get filled with concrete values at runtime — the basis for reproducible LLM calls in applications.
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ReAct (Prompting)
ReAct is a prompting pattern that has an LLM alternate between reasoning (thoughts) and action (tool calls) — the foundation behind many agent implementations.
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Role Prompting
Role prompting assigns the LLM a concrete role or persona ("you are an experienced tax lawyer …") to steer style, vocabulary and depth of answers.
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Self-Consistency
Self-Consistency is a prompting technique where the same question is answered multiple times with chain-of-thought, and the most frequent answer is picked as the final result.
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Self-Refine
Self-Refine is a prompting technique in which a model critiques its own output and improves it across several iterations — without human feedback.
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Spotlighting
Spotlighting is a defense technique against prompt injection in which untrusted inputs are marked so the model treats them as data — not as instructions.
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System Prompt
A system prompt is the instruction that shapes a language model's behavior across an entire conversation — in contrast to the user prompt, which varies per message.
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Tree of Thoughts
Tree of Thoughts (ToT) is a prompting technique in which an LLM explores multiple solution paths as a branching tree, scores them and follows only the promising branches — a generalisation of Chain-of-Thought.
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XML tags in the prompt
XML tags are named brackets like <context>...</context> used to clearly separate sections of a prompt. They structure the input, split instruction from data and make the model's output more predictable.
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Zero-Shot
Zero-shot describes solving a task with a language model without providing any examples — purely via the task description in the prompt.
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