A “full prompt” is a simple yet important concept that describes the optimal state of a prompt, where it includes detailed and complete instructions, all necessary information, and parameters for the AI to generate an accurate and relevant response. This also covers detailed output instructions and format specifications. This ensures the AI has all the information needed to address the request precisely. By eliminating ambiguities and offering clear guidance, a full prompt greatly minimizes the risk of misunderstandings, baseless responses, or errors in the AI’s output, leading to more effective and responses.

Due to the generative characteristic of LLMs’ behavior, which can produce varied outputs, both good and many times bad, challenges arise when users seek precise and accurate answers for a specific purpose. However, they often lack in providing enough detailed instructions. Many times, users focus solely on providing details about the information they want, the question itself, without correctly instructing the model on how to behave, what not to do (negative prompt), They also lack instructions for the desired output format. These gaps lead to inefficient and generic responses, also with regular hallucinations. The ‘full prompt’ concept ensures that prompts contain all the necessary information to fulfill the model’s information requirements to respond in the best possible way, guiding the model’s behavior precisely from start to finish of the interaction cycle by not only asking, but also detailing how to answer and behave… Lets see a pratical example:

So, get in touch with me, and let’s make it happen! I’m currently seeking interesting AI projects and promising prompt challenges.