Documenting code, one commit at a time.
In the rapidly evolving landscape of AI-powered tools, clear communication is paramount. A recent update to the devlog-ist/landing project highlights this necessity, specifically in how these tools interact with platforms like LinkedIn.
AI-generated content, while powerful, often relies on markdown for formatting. However, platforms like LinkedIn don't fully
The devlog-ist/landing project focuses on creating an engaging landing page. Recent efforts have concentrated on refining the visual elements to ensure a clean and focused user experience.
The primary goal was to declutter the landing page and improve its overall aesthetic. This involved removing the lion logo from the LinkedIn banner and simplifying the footer content.
This post discusses an improvement made to the devlog-ist/landing project, specifically addressing how AI-generated content is formatted for LinkedIn. The issue was that markdown links, which are correctly rendered in most contexts, appear as broken plain text on LinkedIn. The solution involved adjusting the AI's instructions to generate plain URLs instead of markdown.
We recently replaced an AI-powered image generation process for our landing page banners with a programmatic rendering solution. While AI initially seemed promising, inconsistencies and errors in the generated images led us to explore alternative approaches. This post details our journey and the benefits of switching to a more controlled and predictable system.
In the fast-paced world of social media, optimizing visual content is crucial for capturing audience attention. This post details our recent effort to improve the performance of LinkedIn banner images for the devlog-ist/landing project, which focuses on developer-related content.
When creating visual assets for LinkedIn, especially banners, it's important to consider how LinkedIn's image compression might affect the final appearance. This post details how we addressed an issue where box-shadows on our landing page banners were causing undesirable compression artifacts after being uploaded to LinkedIn.
When deploying web applications, optimizing assets for social media sharing is crucial. The landing project, which focuses on creating engaging landing pages, recently tackled a common problem: image quality degradation on LinkedIn.
LinkedIn converts uploaded images to JPEG, often resulting in visible pixelation, especially around sharp text and
When creating images for social media, especially for professional platforms like LinkedIn, image quality is paramount. Recompression artifacts can significantly degrade the visual appeal of banners, leading to a less professional look. Here's how we tackled this issue in the devlog-ist/landing project, which, among other things, generates social media banners.
The devlog-ist/landing project focuses on creating landing pages, and a key feature is generating images for sharing on social media platforms like LinkedIn.
Image generation for LinkedIn previews was failing due to an outdated Gemini model ID. The previous model, gemini-2.0-flash-preview-image-generation, was returning a 404 error, preventing the creation of these preview
The devlog-ist/landing project focuses on creating an engaging landing page experience. A recent enhancement involved redesigning the LinkedIn banner to align with a neo-brutalist aesthetic.
The primary goal was to revamp the LinkedIn banner to match the landing page's retro style. This involved incorporating several key design elements:
