Letting GPT-6 Improve My Blog: A Hands-On Test, and a Little About See the Forest

I recently had the opportunity to experiment with GPT-6 and apply it to two rounds of enhancements to my live blog, See the Forest. This blog has experienced multiple design, development, and iteration stages, maintaining its unique product direction and visual style. My objective was to identify potential areas for improvement in this mature project while preserving its distinctive characteristics.

After implementing the changes, more search results appeared on the first screen, mobile articles now featured an expandable table of contents, and the stars and connections appeared sharper.

In the first round, the focus was on improving the reading and search functionalities. Upon examining the search page, it became apparent that the original "Search" heading had ample empty space surrounding it, and higher-ranked results utilized larger text sizes. Additionally, some search snippets replicated their titles, making the page appear imposing while limiting the ability to compare results effectively.

To address these issues, I standardized the font size for result titles, reduced the heading area's space usage, and eliminated snippets that exactly matched their titles. The ranking of search results remained unchanged, and the original content was left unaltered. Similarly, I examined the mobile experience and discovered that the table of contents was hidden on smaller screens.

Furthermore, it was observed that notes beginning with a level-two heading excluded their first section from the table of contents. To tackle these issues, I introduced an expandable table of contents on mobile devices, ensuring that links jump to each section and work even with JavaScript disabled. Additionally, I implemented a retry button for failed searches, added links to topics when no results were found, and rectified a fade-in delay that persisted during reduced motion settings.

During the second round, I sought to make further refinements to the star map's visual appearance. One experiment yielded a cleaner image but resulted in harder-to-recognize topic nodes, so it was not retained. The changes we kept focused on sharper stars, fine lines, and a clearer visual hierarchy of relationships when a node was selected.

Initially, the default view displayed blurry smaller stars and some fine lines. After implementing the refinements, the edges of the stars and fine lines appeared sharper and more discernible. The color scheme remained unchanged, and the nodes had not undergone any rearrangement, but the overall image looked more polished. Additionally, I observed the impact of these changes when selecting a node.

Previously, the main paths connecting the nodes appeared fairly similar in thickness. However, following the visual refinements, the main paths stood out more, while the others were rendered lighter, thereby accentuating the hierarchies within the network.