The article explores the nuances of ASCII rendering, focusing on creating clear and sharp images from ASCII characters. The author built an image-to-ASCII renderer, aiming to improve edge clarity, a common issue in ASCII art. Many existing renderers treat ASCII characters like pixels, leading to blurry and jagged edges. The author illustrates this problem with examples, including a rotating cube animation that highlights poor character contour adherence. To tackle the edge blurriness, the article details the process of image conversion to ASCII. It starts with the basics of mapping lightness values to ASCII characters, using a selection of 10 characters sorted by density. The initial approach, which relied on nearest-neighbor interpolation, resulted in jagged edges due to aliasing artifacts. The author then introduces supersampling as a solution, taking multiple samples within each grid cell to achieve smoother edges. However, this method still produced blurry results because the averaging process neglected the unique shapes of ASCII characters. The core innovation lies in recognizing the shapes of ASCII characters and using them effectively in rendering. By selecting characters based on their visual density and shape rather than just lightness, the renderer achieves sharper and more visually appealing results. This approach enhances the overall quality of ASCII art, allowing for better representation of shapes and contours, ultimately showing how ASCII can transcend the limitations of pixel-based rendering.