Documenting code, one commit at a time.
In our application, we aimed to streamline the user experience by consolidating related settings. Previously, account-specific settings were located on a separate page, leading to potential user confusion. Our goal was to integrate these settings into a more logical and accessible location, simplifying navigation and improving overall usability.
Our application's settings were becoming increasingly complex. The original design placed auto-publish preferences within the Integrations section, which no longer reflected the evolving functionality. To improve usability and maintainability, we decided to move these preferences to a dedicated Automation Settings page.
The existing structure presented several
Adding control over auto-publishing directly within a post generator form can significantly enhance user experience. This post details how we implemented per-generation toggles for platforms like LinkedIn and Dev.to, providing users with granular control over their content distribution.
Previously, auto-publishing settings were managed at the user preference level.
Motivating users to actively participate in referral programs is key to driving growth. A well-designed dashboard widget can significantly increase engagement by providing clear visibility into commission terms, earnings summaries, and accessible sharing options.
Displaying a user's potential earnings and making it easy to share their referral link directly
We've recently enhanced our content generation process by introducing a 'random mode' to our manual post generator. This feature aims to accelerate content creation and reduce repetitive tasks. The primary goal is to automate the selection of post examples and prompts, thereby enabling faster and more varied content output.
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,
This post discusses recent improvements to our application, focusing on enhanced security measures and smarter code generation capabilities.
We've introduced a 'safe mode' feature, giving tenants more control over security audits during post generation. By default, safe mode is enabled, ensuring all generated content undergoes a thorough security check.
In large projects, running the entire test suite can be a significant time sink. Waiting for all tests to pass before merging changes can slow down development and increase feedback loops.
We recently implemented a system to run only the tests related to files changed in a given commit. This dramatically speeds up our test runs and provides faster feedback to developers.
Motivating users to actively participate in referral programs can significantly boost acquisition and growth. We recently enhanced our application's user dashboard with a new widget designed to provide transparent insights into referral earnings and commission structures.
This widget serves as a central hub for users to understand and leverage their referral potential, directly from their
Improving the way we audit code changes is crucial for maintaining security and stability in our applications. Recently, we transitioned from feeding raw Git diffs directly to our AI analysis tools to using structured summaries. This shift significantly enhances auditability and reduces the risk of exposing sensitive information.
Sending raw diffs to AI models
