Lesson 8 15 min

Your 30-Day Open Source Plan

Build your personalized 30-day open source contribution plan — set your goals, choose your first project, create your schedule, and start contributing with AI support.

🔄 Recall Bridge: In the previous lesson, you learned how to build a consistent open source profile — the contribution ladder, sustainable pacing, and how contributions translate to career signals. Now let’s turn everything into your personalized action plan.

You’ve learned the complete open source contribution toolkit: finding projects, understanding codebases, the Git workflow, writing PRs, non-code contributions, and building your profile. This final lesson turns that knowledge into a 30-day plan you’ll start today.

Self-Assessment: Where Are You Starting?

AI prompt for honest assessment:

I want to start contributing to open source. Assess my readiness based on my background: (1) Programming experience: [DESCRIBE], (2) Git knowledge: [NONE/BASIC/INTERMEDIATE/ADVANCED], (3) Languages I know: [LIST], (4) Projects I use daily: [LIST], (5) Available time per week: [HOURS]. Based on this, recommend: which type of first contribution (docs, bug fix, tests, feature), what size project to target, and what my 30-day goal should be.

Starting points by experience level:

Your Level	Best First Contribution	Target Project Size	30-Day Goal
New to coding	Documentation fixes, README improvements	Small (< 1K stars)	1-2 doc contributions merged
Comfortable coding	Bug fixes, test additions	Medium (1K-10K stars)	2-3 contributions of increasing complexity
Experienced developer	Feature implementation, code review	Any size	3-4 contributions + start reviewing PRs

Your 30-Day Plan

Week 1: Setup and Discovery

Day	Task	Time
Day 1	Set up your Git environment and GitHub profile	30 min
Day 2	Browse discovery platforms (Up-for-grabs, CodeTriage, GitHub search)	30 min
Day 3	Evaluate 3-5 projects using the health indicators from Lesson 2	30 min
Day 4	Choose your project, read CONTRIBUTING.md and recent PRs	30 min
Day 5	Clone the project, explore with AI (Lesson 3 workflow)	45 min
Day 6-7	Pick your first issue and start working on it	1 hour

Week 2: First Contribution

Day	Task	Time
Day 8-9	Complete your change and write tests if needed	1-2 hours
Day 10	Self-review with AI, clean up commits	30 min
Day 11	Open your first PR with a detailed description	30 min
Day 12-14	Respond to review feedback, iterate until merged	As needed

Week 3: Second Contribution (Level Up)

Day	Task	Time
Day 15-16	Browse issues for something slightly more challenging	30 min
Day 17-19	Work on the change, using AI for unfamiliar parts	1-2 hours
Day 20-21	Open PR, self-reviewed and polished	1 hour

Week 4: Deepen and Reflect

Day	Task	Time
Day 22-24	Third contribution or help triage issues	1-2 hours
Day 25-26	Review an open PR (practice giving feedback)	30 min
Day 27-28	Update your GitHub profile and resume	30 min
Day 29-30	Plan next month’s contributions	30 min

AI-Powered Accountability

AI prompt for weekly check-ins:

It’s the end of week [N] of my 30-day open source plan. Here’s what I did: [DESCRIBE]. Here’s what blocked me: [DESCRIBE]. For next week, help me: (1) Adjust my plan based on what I learned this week, (2) Find a specific issue to work on next, (3) Identify one skill to focus on improving.

Weekly tracking template:

Week [N] Check-in:
- Contributions submitted: ___
- Contributions merged: ___
- New things I learned: ___
- What blocked me: ___
- Hours spent: ___
- Confidence level (1-10): ___
- Next week's focus: ___

Common First-Month Mistakes

Mistake	Why It Happens	Fix
Starting too big	Excitement, wanting impact fast	First contribution should take < 2 hours
Not reading CONTRIBUTING.md	Impatience to start coding	Spend 10 minutes reading before any code
Working on main branch	Forgot to create feature branch	Make `git checkout -b` your first command
Giving up after rejection	PR feedback feels personal	Feedback = free mentoring from experts
Comparing to others	GitHub profiles of prolific contributors	Compare to your last month, not to anyone else
Irregular schedule	No dedicated time blocked	Block 2-3 hours per week in your calendar

Course Review

What you learned in each lesson:

Lesson	Core Skill	Action
Why Open Source	Understanding the value and AI’s role	Shift mindset from “I’m not good enough” to “I can start today”
Finding Projects	Discover and evaluate projects	Use health indicators, not star count
Understanding Code	Navigate unfamiliar codebases with AI	30-minute exploration workflow
Git Workflow	Fork-branch-commit-PR pipeline	Feature branches, clean commits, rebasing
Pull Requests	Write PRs that get merged	Description template, self-review, feedback response
Non-Code Contributions	Documentation, issues, translations	Start here if code contributions feel intimidating
Building Profile	Sustainable contribution practice	2/month baseline, contribution ladder, career leverage

✅ Quick Check: What’s the single most important thing to remember when starting open source? (Answer: Start. The biggest barrier isn’t skill, tools, or finding a project — it’s the gap between “I want to contribute” and actually doing it. Your first contribution will be imperfect, and that’s expected. The open source community is built on people who started with small, imperfect contributions and kept going.)

Key Takeaways

Focus on depth in your first month: 2-3 progressively complex contributions to 1-2 projects builds more skill and reputation than scattered surface-level contributions across many projects — your second PR to the same project is always better than your first
Use AI to bridge the gap between beginner and regular contributor: when “good first issues” run out, AI breaks down harder issues into manageable steps and helps you understand unfamiliar parts of the codebase so you can take on more challenging work
The hardest part of open source is starting: block time in your calendar, follow the 30-day plan, and remember that every prolific contributor began with a single imperfect contribution — your first PR doesn’t need to be impressive, it just needs to exist

Congratulations

You’ve completed the AI for Open Source Contribution course. You now have the knowledge, tools, and plan to start contributing to open source projects confidently. The next step is simple: open GitHub, find an issue, and make your first contribution today.

Knowledge Check

1. You're creating your 30-day plan. You set the goal: 'Contribute to 10 different projects in the first month.' Is this a good goal?

Yes — diversity shows you can work across different codebases No — breadth without depth in the first month leads to scattered, low-quality contributions. A better goal for month 1: 'Make 2-3 meaningful contributions to 1-2 projects.' This lets you: (1) Learn one project's codebase, conventions, and community, (2) Build a relationship with maintainers who see your name multiple times, (3) Increase contribution depth — your second PR to the same project is always better than your first because you already understand the patterns. After month 1, you can diversify. The first month is about establishing your workflow and building confidence, not maximizing project count It depends on the size of the contributions — 10 typo fixes across 10 projects is fine

2. It's day 15 of your 30-day plan. You've made your first contribution (a documentation fix, merged in 3 days). Now you're stuck — you can't find another issue you feel qualified to tackle. What do you do?

Wait for a good first issue to appear — you don't want to take on something too difficult Use AI to bridge the gap between your current level and slightly harder issues. (1) Browse open issues and pick one that interests you even if it seems a bit beyond your current level. (2) Ask AI: 'This issue asks for [DESCRIPTION]. I've only done documentation fixes so far. Break this down into steps I can follow, explain which files I'd need to understand, and identify which parts are within my skill level vs. which parts I'll need help with.' (3) If you get stuck on a specific part, ask in the issue: 'I'm working on this — I have the basic approach but I'm unsure about [SPECIFIC QUESTION]. Could someone point me in the right direction?' Asking for help shows initiative, not weakness. (4) Growth happens at the edge of your comfort zone — the second contribution should stretch you Switch to a different project — maybe this one doesn't have enough beginner-friendly issues

3. You finished your 30-day plan. You made 3 contributions (1 doc fix, 1 bug fix, 1 test addition), all merged. Your friend made 15 contributions in the same period — all typo fixes. Who got more value from the month?

Your friend — 15 merged PRs looks better than 3 You — because your 3 contributions demonstrate a progression of skills. Doc fix → bug fix → test addition shows you went from surface-level to understanding the codebase. Each contribution was harder than the last, which means you learned more. Progression matters because: (1) Employers see growth trajectory, not just activity, (2) Maintainers notice contributors who increase their depth, (3) Your skills actually improved — you can now read codebases, fix bugs, and write tests in an unfamiliar project, (4) Your next month starts at a higher baseline. 15 typo fixes demonstrate you can use GitHub's web editor; 3 progressive contributions demonstrate you can engineer Neither — open source contributions don't have measurable value

Answer all questions to check

Complete the quiz above first