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
Our application relies on the AutoSyncGeneratePostJob to synchronize data. Recently, we encountered issues with exceeding the rate limits imposed by Azure, leading to job failures and data inconsistencies. To address this, we implemented rate-limiting middleware specifically for this job.
The AutoSyncGeneratePostJob frequently triggered requests to Azure services.
