Documenting code, one commit at a time.
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
This post details the process of seeding initial data, specifically post examples, for tenant-specific features in our application. This approach allows for features like auto-generated posts or random content display that is tailored to each tenant.
When building multi-tenant applications, providing default or example data for each tenant can greatly
