Introduction

We're embarking on the development of SimplexAPI, a new project aimed at simplifying API interactions. This initial phase focuses on setting up the project structure and defining the core components that will drive the API.

Core Functionality

The initial commit lays the groundwork for the entire API. While specific details are not yet implemented, the focus is on:

Introduction

Ensuring the quality of AI-generated content is crucial before it reaches the end user. This post details how we implemented content validation to detect and prevent truncated or incomplete AI-generated posts from being published in the devlog-ist/landing project.

The Problem: Truncated AI Output

AI models, especially when generating longer content, can sometimes be cut off

In the rapidly evolving landscape of AI-powered tools, clear communication is paramount. A recent update to the devlog-ist/landing project highlights this necessity, specifically in how these tools interact with platforms like LinkedIn.

The Problem: Markdown Mishaps

AI-generated content, while powerful, often relies on markdown for formatting. However, platforms like LinkedIn don't fully

Introduction

We've been working on the landing page project which serves as the main marketing site. A key aspect of this project involves streamlining content publishing across multiple platforms. We've recently integrated Dev.to publishing capabilities directly into our Filament admin panel, mirroring our existing LinkedIn publishing workflow.

The Challenge

Previously, publishing

The devlog-ist/landing project focuses on creating an engaging landing page. Recent efforts have concentrated on refining the visual elements to ensure a clean and focused user experience.

The Objective

The primary goal was to declutter the landing page and improve its overall aesthetic. This involved removing the lion logo from the LinkedIn banner and simplifying the footer content.

Introduction

Ensuring the quality of AI-generated content is crucial before it reaches the end user. This post details how to implement automated validation checks to detect and prevent the publication of truncated or incomplete AI-generated articles in the devlog-ist/landing project.

The Challenge

AI models, while powerful, can sometimes produce incomplete outputs due to token limits,

Introduction

We recently replaced an AI-powered image generation process for our landing page banners with a programmatic rendering solution. While AI initially seemed promising, inconsistencies and errors in the generated images led us to explore alternative approaches. This post details our journey and the benefits of switching to a more controlled and predictable system.

Addressing Compression Artifacts on LinkedIn Banners

When creating visual assets for LinkedIn, especially banners, it's important to consider how LinkedIn's image compression might affect the final appearance. This post details how we addressed an issue where box-shadows on our landing page banners were causing undesirable compression artifacts after being uploaded to LinkedIn.

When deploying web applications, optimizing assets for social media sharing is crucial. The landing project, which focuses on creating engaging landing pages, recently tackled a common problem: image quality degradation on LinkedIn.

The Problem: LinkedIn's Recompression

LinkedIn converts uploaded images to JPEG, often resulting in visible pixelation, especially around sharp text and

When creating images for social media, especially for professional platforms like LinkedIn, image quality is paramount. Recompression artifacts can significantly degrade the visual appeal of banners, leading to a less professional look. Here's how we tackled this issue in the devlog-ist/landing project, which, among other things, generates social media banners.

The Problem