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 Goal

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

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 Problem

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.

The Initial Design

Initially, the PostResource table included a column named 'Post Reports'.

Introduction

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

Overview

This update introduces an enhanced referral program with tiered commissions, seamless Dev.to integration, and updated terms and conditions to reflect these changes.

Referral Program Enhancements

The referral program has been expanded with the addition of a dedicated landing page, complete with details about the program, commission rates, and automated tools.

Introduction

This article discusses a common issue in applications using GitHub OAuth for authentication: inadvertently overwriting a user's existing token with one that has fewer permissions. We'll explore how to ensure the application preserves the user's original, broader-scoped token when requesting narrower scopes during subsequent logins.

The Problem

Many applications use GitHub

Introduction

Application performance is often a critical factor in user experience and overall system efficiency. This post delves into several strategies for enhancing performance, focusing on database query optimization, efficient data handling, and code-level improvements.

Database Query Optimization

Inefficient database queries can be a major bottleneck. One common issue is the N+1

Introduction

This post explores several strategies for optimizing data access within an application, focusing on caching and query reduction techniques. Efficient data handling is crucial for maintaining performance, especially as application scale.

Caching Strategies

Caching is a fundamental technique for reducing database load and improving response times.

Introduction

This post details an enhancement to our application's data aggregation process. We addressed an issue where total counts were inaccurate by switching from a local database to an external API for data retrieval, ensuring more reliable results.

The Problem: Data Discrepancies

Previously, our application relied on a local database table, populated with data from an events API,

When interacting with external APIs, especially those with rate limits, it's crucial to implement robust detection mechanisms to prevent service disruptions and ensure smooth operation. A recent adjustment in our application focused on refining the rate limit detection for the GitHub Search API, highlighting the importance of adaptable strategies.

The Problem with Fixed Thresholds