Documenting code, one commit at a time.
In the devlog-ist/landing project, we're focused on delivering high-quality content. A crucial part of this is ensuring that AI-generated content meets our standards before it's published.
AI models, particularly when generating longer pieces of content, can sometimes be cut short due to token limits or other constraints.
This post explores the implementation of cost tracking and budget limits for AI operations within the devlog-ist/landing project. We'll examine how per-request costs are tracked in EUR, how pricing is stored per model, and how monthly cost limits are enforced per plan.
The system now tracks the cost of each AI operation in EUR. This involves:
In the ongoing development of devlog-ist/landing, a project focused on creating engaging landing pages, a recent refactoring effort centered on enhancing the clarity and maintainability of our data structures. Specifically, we focused on the PostResource table.
The original PostResource table included a column labeled 'Post Reports'. This name was ambiguous and didn't clearly
This post delves into a recent refactoring effort within the devlog-ist/landing project, focusing on enhancing the structure and clarity of the PostResource table. The primary goal was to replace the 'Post Reports' column with 'Scheduled For', aiming for a more intuitive and maintainable data model.
Initially, the PostResource table included a column named 'Post Reports'.
This post details the recent enhancements to the content generation process within the devlog-ist/landing project, focusing on the integration and management of LinkedIn prompts for improved content quality and platform-specific tailoring.
The primary objective was to enhance the content generation workflow by incorporating LinkedIn-specific prompts, allowing for more targeted and
Sometimes, seemingly small changes can significantly improve code clarity and maintainability. This post explores a refactoring effort focused on streamlining data representation within a project.
Initially, a particular feature within the devlog-ist/landing project used a column named 'Post Reports' in the PostResource table.
This post details a recent refactoring effort within the devlog-ist/landing project, focusing on improvements to content generation workflows. By separating concerns and enhancing the user interface, we've aimed to create a more maintainable and user-friendly experience.
Previously, the logic for generating content, particularly for platforms like LinkedIn, was tightly
When generating content for LinkedIn using AI, it's crucial to tailor the prompts for conciseness and engagement. The goal is to create posts that fully encapsulate the idea within LinkedIn's character limit, avoiding truncation and maximizing impact.
Key optimizations include instructing the AI to generate short, focused content (around 2500 characters), structured in 3-5 paragraphs.
Working on the landing project, which is focused on creating a compelling user experience, we've recently enhanced our testing strategy to ensure the reliability of our GitHub API integrations.
The goal was to catch potential issues arising from changes to the GitHub API, preventing silent failures in our application. We've implemented a suite of integration tests that validate the structure of
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,
