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Hey everyone! π
I wanted to share the marketing strategy we've been testing for our project, Gitdocs AI, and open the floor for feedback or similar experiences.
Weβre building a tool that helps developers auto-generate high-quality README files using AI, based on the actual content of their GitHub repos. But instead of going heavy on paid ads or traditional promotion, weβre trying a slower, more sustainable path:
Our Current Strategy:- Community-first mindset: Weβve been active in open-source and dev forums, not promoting the tool, just genuinely helping folks write better docs.
- Content > Ads: Weβve started a blog + mini-guides (like βHow to structure a great READMEβ) to provide value without selling anything.
- Dogfooding: Every update we make to the tool is something we document and share transparently on Twitter/LinkedIn, focusing on what weβre learning.
- Feedback loop: Early testers are shaping the roadmapβthis has led to more organic interest than we expected.
- Cold outreach via LinkedIn (even thoughtful messages) mostly felt inorganic.
- Reddit can be great, but we had one post flaggedβeven though it wasnβt promoβso we're being extra cautious now.
Would love to hear from others working on dev tools or bootstrapping products:
π§ What has worked for you in building awareness authentically?
Letβs make this thread a goldmine for early-stage marketing ideas that donβt rely on ads or spam π

Hey everyone! π
Super excited to finally share something Iβve been building over the past few weeks β Gitdocs AI.
π§ What is it?Gitdocs AI is a developer tool that analyzes the structure and content of a GitHub repository and generates a clean, professional README file using AI. It's designed to help devs ship better documentation without spending hours figuring out what to include or how to format it.
βοΈ How it works:- GitHub Integration: Users connect their repo, and the tool fetches metadata, file structure, and key code files.
- AI Analysis: It uses natural language generation (via locally run models or API-based, depending on setup) to generate a README draft with installation steps, usage instructions, features, and contribution guidelines.
- Customization Options: Users can tweak the tone (casual, professional, etc.) or focus areas (e.g., installation-heavy vs. feature-focused).
- One-Click Commit: The final README can be committed directly to the repo after review.
- Frontend: Next.js + Tailwind
- Backend: Node.js, Python (for AI processing), GitHub API
- Database: Supabase
- AI Integration: Custom prompt pipelines + optional Ollama local model support
README files are often overlooked, yet theyβre the first thing people see. As someone who jumps between side projects, I found myself procrastinating the docs every single time. This was my attempt to solve that friction point β for myself and maybe for others too.
Would love your thoughts, suggestions, or even tough love if you spot something I could improve.
Thanks for reading! π




