Multimodal Large Language Models (MLLMs) are rapidly approaching human-level visual understanding. However, they sometimes miss the mark, especially when it comes to fine details or small objects in images. This "Amblyopia" effect, as researchers call it, hinders an MLLM's ability to truly grasp the nuances of an image. Enter Panther, a new approach that aims to give MLLMs the sharp vision of their namesake. Panther integrates user instructions directly into the visual processing pipeline, guiding the model's attention to the most relevant parts of the image. Imagine asking an MLLM, "Is there a ring on the person's finger?" A typical MLLM might get distracted by other elements in the scene. Panther, however, uses the instruction as a visual prompt, focusing its attention directly on the hand and seeking the ring. This instruction-guided approach is achieved through three components: Panther-VE, Panther-Bridge, and Panther-Decoder. The Panther-VE acts as the initial filter, using instructions to generate focused visual data. Think of it as highlighting the key areas of an image based on what you're looking for. The Panther-Bridge then steps in for multi-turn conversations, cleverly removing redundant visual information between turns. This saves significant processing power and time, preventing the model from getting bogged down with unnecessary data. Finally, the Panther-Decoder integrates these enhanced visuals with the language model to generate accurate and insightful responses. This versatile decoder works with various LLMs, making Panther a flexible solution. Testing across various benchmarks, including visual question-answering, showed Panther consistently outperforms existing MLLMs, particularly in tasks demanding precise visual understanding. The results are particularly promising for vision-centric tasks, suggesting that Panther's focused visual processing significantly improves the model's comprehension of images. For example, Panther excels at spotting subtle details like the direction of light in a cityscape, demonstrating its refined visual acuity. While still a research project, Panther offers exciting potential for future applications. From medical image analysis to improved virtual assistants, guiding the attention of MLLMs with more precision promises to unlock their full potential for understanding our visual world.