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.

Smarter AI suggestions that read and match your text annotations

Our AI can now understand the actual words in your text annotations to offer up to three tailored design options per category, matching your style more closely than before.

This update makes our AI assistant much better at interpreting your design notes. Instead of just recognizing annotation types, it now reads the actual text you add, like “fence” or “lighting,” giving you richer, more relevant suggestions.

More personalized design ideas
By analyzing the text content of your annotations alongside the overall style of your canvas—whether modern, rustic, or traditional—the AI can suggest up to three different options per category. This means you get a variety of choices that truly fit your vision.

Clearer insight into suggestions
We’ve improved the way materials and text annotations are logged separately so you can better understand how the AI arrives at its recommendations. Even when relying on text alone, the suggestions now embrace the nuances of your annotations, making your design process smoother and more inspired.