What is build in public and why should I do it?

Building in public means sharing your development journey on social media as you build your product. It helps you grow an audience, get early feedback, build credibility, and create marketing momentum before you even launch.

How does Makrly generate posts from my commits?

When you push code to GitHub, Makrly reads your commit messages and code changes. Our AI analyzes what you built, filters out mundane commits, and generates engaging social media posts tailored for each platform.

Is my code safe? What permissions do you need?

Yes, your code is safe. We only request read-only access to your repositories. We can't modify your code, create branches, or make any changes. We only read commit messages and diffs to understand what you're building.

Can I use my own AI API key?

Yes! You can bring your own API key from OpenAI, Anthropic Claude, Google Gemini, or other providers through OpenRouter. This gives you full control over which AI model generates your posts.

Which platforms are supported?

Currently, Makrly generates posts optimized for X (Twitter), LinkedIn, and Facebook. Each platform gets a different version tailored to its audience and format.

Searchable placement filter makes report browsing faster

You can now quickly find reports for specific placements with a new searchable dropdown that updates dynamically based on your site selection.

We’ve added a new searchable placement filter to the reports page to help you find exactly what you’re looking for without hassle. Instead of scrolling through long lists, you can now type to quickly locate the placement you want, streamlining your workflow.

Smarter filtering that adapts to your site
The placement filter doesn’t just show names — it pairs them with their corresponding sites for clarity, and it automatically updates when you change the site filter. This means you’ll always be working with relevant, up-to-date options to zero in on the reports that matter most.

This improvement is all about saving you time and cutting through the noise so you can focus on analyzing your data more efficiently.