Documenting code, one commit at a time.
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.
This post details a small but important change in how we generate content for sharing on LinkedIn, focusing on aligning the tone with the platform's user experience.
The primary goal was to shift the voice of automatically generated LinkedIn share posts to a first-person perspective. Since the posts are published from the user's profile, using "I" instead of third-person references
We recently added a "Share on LinkedIn" feature to our landing page project, devlog-ist/landing. The goal was to increase user engagement and expand the reach of user portfolios by enabling seamless sharing on LinkedIn. This post details the implementation process, covering AI-powered post generation, direct publishing via the LinkedIn API, and considerations for different user
Improving the auditability of AI interactions is crucial for maintaining security and control. A recent update focuses on preventing the exposure of raw code to AI models, enhancing data security, and providing better insights into flagged code changes.
Previously, raw git diffs were sent to AI models for analysis. This approach, while providing detailed context,
