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JavaScript Python

Streamlining Content Generation with LinkedIn Prompts in Devlog-ist/landing

This post details the recent enhancements to the content generation process within the devlog-ist/landing project, focusing on the integration and management of LinkedIn prompts for improved content quality and platform-specific tailoring.

The Goal

The primary objective was to enhance the content generation workflow by incorporating LinkedIn-specific prompts, allowing for more targeted and

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PHP SEO

Boosting SEO on the Landing Page

The devlog-ist/landing project focuses on creating a compelling landing experience. Recent work centered on improving SEO and ensuring proper sitemap discovery.

The Problem

The Cloudflare CDN was overriding the application's robots.txt, which prevented search engines from discovering the sitemap. This negatively impacted SEO performance.

The Approach

To bypass the CDN override, a

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PHP Laravel Symfony

Enhancing Email Notifications with Transactional Headers and Code Style Improvements

Introduction

In our ongoing effort to improve the reliability and traceability of email communications within our application, we've recently implemented transactional email headers for recommendation notifications. This, coupled with some code style enhancements, aims to provide a more robust and maintainable system.

Transactional Email Headers

Transactional emails, such as

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Enhancing Technology Detection in Post Generation

Improving the accuracy and scope of technology detection is crucial for generating relevant and informative content. A recent update introduces rule-based technology detection, significantly expanding our ability to identify the technologies involved in code changes. This enhancement allows for more precise tagging and categorization of blog posts, benefiting both content creators and readers.

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Content Negotiation for AI Agents: Serving Markdown

Our application now supports content negotiation to better serve AI agents and LLMs. We've added the ability to return Markdown instead of HTML when requests include the Accept: text/markdown header.

This enhancement allows AI agents to directly consume the raw Markdown content of our posts, simplifying parsing and improving efficiency.

The Problem

Previously, our application served HTML

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PHP Laravel SEO

Canonical URLs and SEO: Ensuring Consistent Indexing

Maintaining a consistent URL structure is crucial for search engine optimization (SEO). Duplicate content, even with slight variations in the URL (like the presence or absence of "www"), can confuse search engines and dilute your website's ranking potential.

The Problem: Duplicate Content with Varying URL Prefixes

Search engines like Google treat example.com and `www.example.

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Enhancing AI Auditability Through Structured Summaries

Improving the auditability of AI interactions is crucial for maintaining security and control. A recent update focuses on preventing the exposure of raw code to AI models, enhancing data security, and providing better insights into flagged code changes.

The Challenge of Raw Diffs

Previously, raw git diffs were sent to AI models for analysis. This approach, while providing detailed context,

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Python JavaScript

Adding a Safe Mode and Improving Code Generation

This post discusses recent improvements to our application, focusing on enhanced security measures and smarter code generation capabilities.

Safe Mode Implementation

We've introduced a 'safe mode' feature, giving tenants more control over security audits during post generation. By default, safe mode is enabled, ensuring all generated content undergoes a thorough security check.

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Enhancing AI Auditability: From Raw Diffs to Structured Summaries

Improving the way we audit code changes is crucial for maintaining security and stability in our applications. Recently, we transitioned from feeding raw Git diffs directly to our AI analysis tools to using structured summaries. This shift significantly enhances auditability and reduces the risk of exposing sensitive information.

The Problem with Raw Diffs

Sending raw diffs to AI models

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