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.

The Problem: Silent Content Truncation

AI models, particularly when generating longer pieces of content, can sometimes be cut short due to token limits or other constraints.

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

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

The devlog-ist/landing project focuses on creating landing pages, and a key feature is generating images for sharing on social media platforms like LinkedIn.

The Problem

Image generation for LinkedIn previews was failing due to an outdated Gemini model ID. The previous model, gemini-2.0-flash-preview-image-generation, was returning a 404 error, preventing the creation of these preview

Introduction

This post explores how to enhance the automatic generation of LinkedIn banner images by including technology badges and a portfolio URL. This provides a richer, more informative visual representation for professional profiles.

Problem

Previously, the generated LinkedIn banner image only contained the person's name and position. This lacked context about their technical

Introduction

When integrating AI into software development workflows, it's crucial to handle potential inconsistencies in the AI's responses. This post addresses a scenario where an AI service, designed to provide structured data, occasionally omits a specific key, leading to errors in the consuming application.

The Problem: Missing mermaid_diagram

The devlog-ist/landing project

We're constantly striving to improve the content generation process for the devlog-ist/landing project, which aims to create engaging and informative landing pages. Recently, we focused on enhancing the AI's ability to generate relevant diagrams for our technical blog posts. It turns out simply asking for a diagram isn't enough – you need to be specific about its purpose!

The Problem: Generic

Introduction

In the ongoing development of devlog-ist/landing, a project whose description was not provided, maintaining a consistent brand identity and relevant content presentation is crucial. This post explores recent enhancements focused on visual consistency in LinkedIn banner generation using brand colors, a white logo, and top tags by frequency.

Enforcing Brand Color Palette