Documenting code, one commit at a time.
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 primary objective was to enhance the content generation workflow by incorporating LinkedIn-specific prompts, allowing for more targeted and
The devlog-ist/landing project focuses on creating a compelling landing experience. Recent work centered on improving SEO and ensuring proper sitemap discovery.
The Cloudflare CDN was overriding the application's robots.txt, which prevented search engines from discovering the sitemap. This negatively impacted SEO performance.
To bypass the CDN override, a
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.
Search engines like Google treat example.com and `www.example.
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.
Previously, raw git diffs were sent to AI models for analysis. This approach, while providing detailed context,
This post discusses recent improvements to our application, focusing on enhanced security measures and smarter code generation capabilities.
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.
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.
Sending raw diffs to AI models
We've recently rolled out enhancements to our post generation process, focusing on flexibility and code accuracy. These updates include a 'safe mode' toggle and intelligent programming language detection.
Recognizing that different tenants have varying security needs, we've introduced a 'safe mode' toggle.
Security audits are crucial for maintaining the integrity of applications. However, overly sensitive rules can lead to false positives, particularly when dealing with illustrative code examples. This post discusses how to refine audit rules to distinguish between genuine security vulnerabilities and intentionally simplified or educational code snippets.
Auditing tools are crucial for maintaining application security and compliance. However, false positives can create unnecessary noise and divert attention from genuine threats. One common source of these false positives is the detection of reserved domain names, such as those under the IANA's example.com, example.net, and example.
In software development, a robust workflow is crucial for maintaining code quality and minimizing potential issues. Recently, we've focused on refining our development process to incorporate more rigorous code review practices, specifically before finalizing changes.
Integrating a 'dev:code-review' step earlier in the workflow offers several key advantages:
