Prompt injection in speech recognition is a novel technique that enhances Automatic Speech Recognition (ASR) by guiding the underlying model to produce more accurate transcriptions through context-setting. This method, which can be seen as a giant magnet influencing the interaction of tokens or features in the model's latent space, allows the decoder to prioritize certain words that align with the context provided by the prompt. By altering these interactions, prompt injection can help differentiate between words that are acoustically similar but contextually distinct, such as "fiber" and "cider," depending on the conversation's subject matter. This technique complements existing methods like keyword boosting and speech adaptation, offering a new dimension to improving the quality of audio transcription. While it holds promise for advancing ASR technology, it also carries potential risks if not used responsibly.