Free Practice Questions for WGU Practical-Applications-of-Prompt Exam

The phrase "Find bike paths near Minneapolis" functions as theInstructionscomponent of the prompt. Instructions are the direct commands given to the AI, specifying the primary task that the user wants the system to perform. In any effective prompt, the instruction is the "verb" or the "action" that initiates the AI’s processing. Without clear instructions, the AI may understand the subject (bike paths) and the location (Minneapolis) but may not know whether it should list them, map them, describe their history, or compare their difficulty levels.

In this specific case, the word "Find" is the directive. While "Minneapolis" provides a geographical constraint (Context), the core of the statement is the command to locate specific data. Effective prompt engineering relies on being explicit with these instructions to avoid ambiguity. For instance, a more refined instruction might be "Provide a list of..." or "Summarize the locations of..." to further clarify the desired action. However, at its most basic level, this component tells the AI exactly what operation to execute on the provided information, making it the functional heart of the prompt.

One of the most significant and persistent challenges in the field of Artificial Intelligence is the lack of inherent ethical reasoning. AI models operate based on mathematical probabilities and patterns found within their training data; they do not possess a moral compass, a sense of justice, or an understanding of social nuances unless specifically programmed or constrained by human-defined rules. This often leads to issues where an AI might generate biased, harmful, or socially insensitive outputs because it is simply reflecting the biases present in its training set without any ethical filter.

While AI is actually quite proficient at analyzing vast amounts of data and is increasingly capable of processing unstructured data and generating video, the "black box" nature of its decision-making makes ethical alignment difficult. Ensuring that an AI respects privacy, avoids discrimination, and adheres to human values requires significant external intervention, such as Reinforcement Learning from Human Feedback (RLHF). The challenge lies in the fact that ethics are often subjective and context-dependent, making it nearly impossible to encode a universal moral code into a machine. This lack of ethical reasoning is why human oversight remains a critical component of AI deployment, especially in high-stakes fields like law, healthcare, and autonomous systems.

Incorporating detailed descriptions within a prompt is a fundamental practice in prompt engineering that leads to thebetter articulation of user needs. When a user provides a high level of detail, they are essentially mapping out their mental model for the AI. Generative AI models function by predicting the most statistically likely response based on the input provided; therefore, the more specific the input, the more "locked in" the AI becomes to the user's specific intent. Detailed descriptions help remove ambiguity, ensuring the AI doesn't have to "guess" what the user wants.

For example, instead of asking for a "business plan," a detailed description would specify the industry, target audience, funding goals, and specific competitive advantages. This allows the AI to align its output exactly with the user's requirements. While detailed prompts can occasionally help reduce certain types of errors (Option B), their primary strength lies in communication clarity. It bridges the gap between a vague idea and a concrete output. In practical applications, this reduces the number of iterations required to reach a final product, as the AI receives a clear set of requirements from the start, leading to a much more useful and tailored result.

The most critical step in the "pre-prompting" phase is the clear identification of the objective. Before interacting with a generative AI, the user must identify the goal of the speech. This foundational step dictates every other element of the prompt, including the persona, tone, and specific constraints. For example, a speech intended to persuade a group of investors requires a radically different linguistic approach than a speech intended to toast a friend at a wedding.

By identifying the goal first, the user can construct a prompt that provides the AI with a clear "definition of success." In practical applications, this is often referred to as the "Intent" phase. If a user skips this and goes straight to writing a draft or providing samples, the AI may generate content that is stylistically correct but fundamentally misses the mark regarding the intended outcome. Clear goals allow the user to evaluate the AI's output critically—checking if the generated text actually serves the purpose of informing, persuading, entertaining, or inspiring. Without a defined goal, prompt engineering becomes a trial-and-error process rather than a strategic exercise.

Midjourneyis a generative AI tool that specifically specializes in high-quality, versatile image creation through sophisticated text prompts. While other tools like DALL-E are integrated into larger ecosystems (like OpenAI's ChatGPT), Midjourney has gained a reputation for its distinct artistic style, high resolution, and deep "parameter" controls that allow prompt engineers to fine-tune lighting, camera angles, and textures.

Midjourney operates primarily through a Discord interface, where users utilize "slash commands" (like /imagine) to initiate generations. It is favored by designers and concept artists because of its ability to interpret complex, evocative language into visually stunning outputs. Unlike ChatGPT, which is primarily a text-based LLM, Midjourney is a "Diffusion Model" specifically trained on image-caption pairs. Evaluating Midjourney as a medium requires understanding that the "syntax" of the prompt differs from text models; it relies heavily on artistic descriptors, style references (e.g., "unreal engine," "octane render"), and aspect ratio constraints to achieve the desired outcome.