Prompt Engineering

A prompt engineer is designing a system prompt for a customer support agent. The goal is to ensure the agent always responds in a polite, professional tone and never provides medical advice. Which approach best achieves this?

A developer needs to extract structured data from news articles in JSON format, but the model occasionally outputs extra fields or omits required fields. Which prompt engineering approach would MOST reliably enforce the exact schema?

A prompt engineering team is designing a system prompt for a chatbot that should adopt a professional and concise tone. Which prompt pattern is BEST suited for this requirement?

A prompt engineer is refining a prompt that currently produces outputs with excessive repetition. Which TWO parameters can be adjusted to reduce repetition? (Choose two.)

Which prompt pattern is most suitable when a user needs to generate a structured report following a specific template every time?

When using Cohere Command models on OCI Generative AI, a developer wants to ground a response based on a provided document. Which syntax should be used to embed document content in the prompt?

A team wants to use a prompt pattern that combines reasoning with acting, where the model alternates between thinking and taking actions (e.g., tool calls). Which pattern fits this requirement?

A data scientist wants to generate a response that lists top-3 product features in a bulleted format with no introductory text. Which prompt engineering technique should be used?

A team is prompting a model to translate English to French. They notice the model occasionally mixes French with other Romance languages. Which prompt refinement strategy would MOST likely improve language consistency?

A team wants to create a prompt library for their organization's LLM applications. Which practice is MOST important for maintaining prompt quality over time?

A prompt engineer is designing a system to answer customer queries using OCI Generative AI. They want to ensure the model's responses are concise, accurate, and consistent. Which TWO prompt engineering practices should they implement? (Select two.)

A developer uses a Cohere Command model with a preamble: 'You are a helpful assistant that answers questions based on the provided document.' They also include a user message with a query and a relevant document excerpt. However, the model often ignores the document and uses its own knowledge. Which improvement is MOST effective?

Which prompting technique involves providing the model with a few examples of input-output pairs within the prompt to guide its behavior?

A developer is using Cohere Command R+ via OCI Generative AI and wants to ground answers in a provided set of documents using the `documents` parameter. Which prompt structure ensures the model correctly adheres to the documents?

A prompt engineer is using the self-consistency technique to improve answer reliability. Which TWO steps are essential when implementing self-consistency?

An AI engineer is designing a prompt that requires the model to solve a complex math problem. They want the model to explore multiple reasoning paths and then aggregate the final answer. Which prompting technique BEST fits this requirement?

A data scientist is iteratively refining a prompt for a text classification task. Which TWO practices are essential for systematic prompt improvement?

An engineer is using the ReAct pattern to build a reasoning agent. The agent should first reason about the user query, then call an external API, and finally incorporate the API result into a final answer. Which prompt structure best implements this pattern?

A prompt engineer is tasked with reducing hallucinations in a document-grounded generation task using Cohere Command R. Which system prompt component is MOST effective for enforcing that the model only uses provided documents?

Which prompt engineering technique asks the model to explain its reasoning process step-by-step before arriving at the final answer?

A developer is using the ReAct pattern to build a reasoning agent. Which of the following best describes the two main steps in this pattern?

A prompt engineer is iteratively refining a prompt for a product review summarizer. They want to test which prompt version yields the most accurate summaries. Which approach should they use?

A prompt engineer wants the model to adopt a formal and authoritative tone when generating financial reports. Which approach is MOST effective?

A data scientist is using self-consistency decoding to improve the accuracy of a reasoning task. Which of the following best describes the process?

A developer is tuning parameters for a text-generation model and wants to reduce the likelihood of the same phrase appearing repeatedly. Which parameter should be adjusted?

A prompt engineer wants to generate a poem in a specific rhyming scheme (ABAB). Which combination of prompt components is LEAST likely to succeed?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Which parameter controls the randomness of the model's output by adjusting the probability distribution of the next token?

A prompt engineer is developing a multi-step reasoning application using the ReAct pattern. The model sometimes outputs incomplete reasoning or forgets to perform an action. Which improvement to the prompt is MOST likely to address this issue?

A prompt engineer wants to reduce the model's tendency to generate overly creative or off-topic responses when summarizing financial reports. Which parameter adjustment is MOST appropriate?

A prompt engineer is iteratively refining a prompt for a summarization task. Which THREE practices should she adopt to improve prompt performance systematically?

A prompt engineer notices that the model's output frequently repeats the same phrases. Which parameter adjustment is MOST likely to reduce this repetition?

A prompt engineer wants to use chain-of-thought prompting to improve arithmetic reasoning. Which TWO steps are essential for implementing this technique?

A developer is using the Cohere Command model via OCI Generative AI and wants to ground responses in a specific uploaded document. Which syntax should be used in the preamble to enable document-grounded generation?

A prompt engineer is designing a system that generates SQL queries from natural language. The model sometimes produces unsafe queries (e.g., DROP TABLE). Which constraint in the system prompt would BEST mitigate this risk?

A prompt engineer is using the ReAct pattern to enable the model to reason and act (e.g., call tools). Which THREE components are essential in the prompt to implement ReAct correctly?

A prompt engineer is testing a new prompt for a Q&A system. The prompt includes ambiguous wording that causes the model to answer inconsistently. Which TWO steps should the engineer take to resolve this? (Choose two.)

An organization maintains a library of prompt templates for various use cases. Which three practices are essential for effective prompt management? (Choose three.)

A prompt engineer is designing a ReAct pattern prompt to enable an LLM to use external tools. Which of the following is a key characteristic of the ReAct pattern?

An LLM application generates product descriptions. The output is sometimes repetitive (e.g., 'innovative' appears multiple times). Which parameter adjustment is MOST likely to reduce this repetition without harming creativity?

A data scientist is designing a prompt to generate a structured report with sections for Summary, Findings, and Recommendations. Which output format specification in the prompt would be MOST effective?

What is the PRIMARY purpose of the 'stop sequences' parameter in text generation?

A team is troubleshooting a chatbot that sometimes outputs harmful content despite having a system prompt with safety instructions. Which THREE measures should they implement to reduce the risk?

An AI application uses chain-of-thought prompting to solve math problems. The team observes that the model sometimes arrives at correct answers but with flawed reasoning. Which technique can specifically help by aggregating multiple reasoning paths?

Which of the following is an example of a prompt template?

A developer wants the model to generate a bullet list of steps to troubleshoot a network issue. Which output format specification should be included in the prompt?

What is the primary goal of chain-of-thought prompting?

A developer is using tree-of-thought prompting to solve a complex planning problem. Which THREE characteristics are typical of tree-of-thought?

What is the primary purpose of setting the 'top-k' parameter in an LLM?

What is the primary purpose of setting a low temperature (e.g., 0.1) when generating text with an LLM?

What is the main advantage of using chain-of-thought (CoT) prompting over standard few-shot prompting for complex reasoning tasks?

Which THREE are common prompt failures that can degrade model performance?

A prompt engineer wants to generate a JSON object from an LLM response. Which prompt component is MOST critical to ensure the output is valid JSON?

A prompt engineer is designing a prompt for legal document analysis. The model should output JSON with a specific structure. Which TWO practices are essential to include in the prompt?

A developer is using the Cohere Command R model with a preamble set to "You are a helpful assistant." The user message contains a question. The model's response is factual but lacks detail. To encourage more comprehensive answers, which modification should be made?

A developer is using Cohere Command R with document-grounded generation. Which THREE elements must be included in the prompt to enable effective document grounding?

A prompt engineer wants the LLM to adopt the persona of a 'friendly customer support agent' for all interactions. Which approach is most effective?

A company wants to use Cohere Command for a customer support chatbot that references a knowledge base. The chatbot must maintain conversational context across multiple turns. Which TWO Cohere-specific features should they use?

A prompt engineer is testing different versions of a prompt to improve accuracy on a classification task. Which practice is most appropriate for systematic refinement?

A prompt engineer is designing a system that must extract structured data from unstructured text. The model occasionally outputs extra text beyond the required JSON. Which parameter should be adjusted to enforce strict output format?

A developer is using a Cohere Command model via OCI Generative AI. They want the model to generate responses strictly in JSON format for a specific task, but the model sometimes outputs additional explanatory text. Which prompt engineering technique is MOST effective?

In OCI Generative AI, when using the Cohere Command model, which parameter is used to discourage the model from repeating the same phrases?

A data scientist is designing a prompt for code generation and needs to reduce the likelihood of the model generating incorrect or hallucinated code. Which two parameter adjustments are most effective? (Choose two.)

Which prompting technique involves providing the model with a small set of input-output examples within the prompt to guide its behavior?

A developer is using a prompt template that includes placeholders like {context} and {question}. They want to version these templates for A/B testing. Which practice is BEST for managing prompt templates?

A prompt engineer is designing a system that generates step-by-step recipes for users. Which TWO prompt patterns are MOST relevant for this task?

A developer is using chain-of-thought prompting to solve a multi-step math problem. The model produces an incorrect final answer, but the intermediate reasoning steps appear logical. Which technique should be applied to improve accuracy?

A prompt engineer wants to ensure the model outputs a JSON object with specific keys. Which prompt component is most appropriate to specify this requirement?

A developer notices that an LLM occasionally generates harmful or biased responses despite a system prompt instructing it to be safe. Which technique can help mitigate this at inference time without retraining?

Which of the following is a common prompt injection vulnerability?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Which scenario BEST describes a prompt injection vulnerability?

A data scientist wants to generate a concise summary of a long legal document. The model should output a bullet list of key points. Which prompt component is LEAST important for this task?

A team is iteratively refining a prompt for a summarization task. Which THREE activities are essential for effective iterative prompt refinement?

A company uses OCI Generative AI to generate product descriptions in XML format. The engineer wants to improve adherence to the XML schema. Which THREE prompt components are most critical? (Select three.)

Which TWO parameters directly control the randomness and diversity of generated tokens?

A developer is using Cohere Command to answer questions grounded in internal technical manuals. They want to ensure the model only answers based on the provided documents and does not use its pre-trained knowledge. Which Cohere-specific technique should be applied?

Which prompting technique involves generating multiple independent reasoning paths and then selecting the most common answer?

An OCI user is troubleshooting a prompt that sometimes produces outputs containing offensive language. The prompt uses a system prompt to set a professional tone. Which THREE steps should the user take to mitigate this issue? (Select three.)

What is the primary benefit of using a system prompt to set the persona and tone before the user message?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

Which parameter controls the randomness of the model's output by scaling the probability distribution before sampling?

Which prompting technique involves providing the model with a small number of input-output examples within the prompt to guide its behavior?

An application uses an LLM to summarize legal documents. The summaries sometimes include hallucinations (details not in the original text). Which prompt engineering technique is MOST effective at reducing hallucinations?

An AI engineer is designing a prompt to generate a report summary. The prompt currently says: 'Summarize the following text.' The output is often too verbose. Which modification would best enforce a concise, bullet-list format?

During iterative refinement, a prompt engineer tests two prompt variants on the same 100 inputs and measures accuracy. Variant A yields 85% accuracy, Variant B yields 82%. However, Variant B's outputs are more concise and preferred by users. What should the engineer do NEXT?

Which parameter controls the creativity and randomness of a model's output by adjusting the probability distribution before sampling the next token?

A company is building a chatbot that must maintain a professional tone and avoid discussing off-topic subjects. Which TWO prompt engineering approaches should they combine to enforce these requirements?

A data scientist is using OCI Generative AI to generate synthetic data for training. They observe that the model's outputs lack diversity and often repeat the same phrases. Which combination of parameter adjustments would BEST increase output diversity?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A practitioner is developing a legal document summarization system and needs to reduce hallucinations. Which prompting technique is most effective for improving factual accuracy by exploring multiple reasoning paths?

A prompt engineer is troubleshooting a chatbot that consistently fails to follow instructions when the user includes adversarial input. Which two strategies can mitigate prompt injection attacks? (Choose two.)

Which TWO are benefits of using few-shot prompting compared to zero-shot prompting?

A prompt library manager wants to implement version control for prompt templates used across multiple applications. Which THREE practices should they adopt?

A developer wants the LLM to solve a math problem by reasoning step by step. Which prompting technique should they use?

When tuning the temperature parameter for a text generation task, which effect does setting temperature to 0.1 have compared to 0.9?

An organization wants to ensure that prompts submitted to an LLM do not contain sensitive customer data. Which practice is most effective?

Which TWO are best practices for prompt management in production environments?

During iterative prompt refinement, a team evaluates two prompt variants on 100 test queries. Variant A scores 85% accuracy but occasionally generates offensive content. Variant B scores 80% accuracy with no safety issues. Which evaluation criterion should take priority for a customer-facing application?

A prompt engineer notices that the model sometimes generates outputs that include parts of the system prompt or user message verbatim. This is likely a symptom of which common prompt failure?

In few-shot prompting, what is the primary purpose of including examples in the prompt?

A prompt engineer is testing two versions of a prompt for a content generation task. They want to measure which version produces more factual and concise outputs. Which evaluation approach is BEST?

A user repeatedly gets the same phrase output by the model. Which parameter adjustment is MOST likely to reduce such repetitive patterns?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

An OCI Generative AI user notices that a model generates repetitive phrases when summarizing technical articles. Which parameter adjustment is MOST likely to reduce this repetition?