Skip to main content
OpenSource Together uses AI-powered recommendations to help you discover the perfect open-source projects that match your technical skills, interests, and career goals.

How AI Recommendations Work

The platform analyzes your profile data to provide personalized project suggestions:
  1. Onboarding Profile: During onboarding, you share your job title, technical skills (up to 10), and interests (up to 6 categories)
  2. Skill Matching: The AI matches your tech stack with project technologies
  3. Interest Alignment: Your selected categories are compared against project classifications
  4. Continuous Learning: AI-suggested categories improve over time as the system learns

Personalized Discovery

Get project recommendations based on your unique profile and preferences

Tech Stack Matching

Find projects using technologies you already know or want to learn

Interest-Based Filtering

Discover projects in categories that align with your passions

Smart Suggestions

AI learns from community patterns to improve recommendations over time

Setting Up Your Profile

To receive accurate recommendations, complete your onboarding profile:

Job Title

Share your professional role to help the AI understand your experience level and focus areas.
Example: Fullstack Developer, Backend Engineer, DevOps Specialist

Technical Skills

Select up to 10 technologies from your tech stack. The platform matches these with project requirements.
Choose technologies you’re comfortable with or eager to learn. Projects using these technologies will be prioritized in your recommendations.

Interests and Categories

Pick up to 6 categories that represent your interests, such as:
  • Web Development
  • Machine Learning
  • DevOps & Infrastructure
  • Mobile Development
  • Security & Privacy
  • Developer Tools
AI-suggested categories may not be perfectly accurate initially but will improve as the system learns from your interactions and community patterns.

Benefits of AI Recommendations

Faster Project Discovery

Instead of manually searching through hundreds of projects, the AI surfaces the most relevant options based on your profile.

Better Project-Contributor Fit

Recommendations consider both your existing skills and learning interests, helping you find projects where you can make meaningful contributions.

Reduced Decision Fatigue

The AI filters out irrelevant projects, so you can focus on opportunities that truly match your goals.

Improving Your Recommendations

Your recommendations become more accurate over time. To optimize them:
  1. Keep Your Profile Updated: Regularly update your tech stack and interests as they evolve
  2. Interact with Projects: Bookmark projects you’re interested in to help the AI learn your preferences
  3. Explore Different Categories: Browse various project types to expand your recommendation range
The more complete and accurate your profile, the better your personalized recommendations will be.

How It Integrates with Discovery

AI recommendations work alongside the project discovery features:
  • Trending Projects: See what’s popular in your areas of interest
  • Tech Stack Filtering: Refine recommendations by specific technologies
  • Category Browsing: Explore projects within your favorite categories
  • Custom Ordering: Sort recommended projects by recency, name, or trending status
The combination of AI-powered recommendations and manual filtering gives you complete control over your project discovery experience.

Build docs developers (and LLMs) love