How I Earned $10 on GitHub Using AI Agents (Without Writing a Single Line of Complex Code)

I've been exploring the world of open source bounties — getting paid for contributing to open source projects. After submitting 17 PRs and earning my first $10, here's exactly how I did it with the help of AI coding agents.

The Setup

I use Hermes Agent (an open-source AI agent by Nous Research) to automate the tedious parts: searching for bounty issues, understanding the codebase, writing PRs, and tracking progress.

The key tools:

• Hermes Agent — CLI-based AI agent with tool access
• GitHub PAT (Personal Access Token) — for API access
• Stripe Connect — for receiving payments
• Platforms: Opire (0% fee, dev-friendly), Algora, BountyHub

Step 1: Finding Bounties

The hardest part is knowing where to look. I automated it:

# Search for bounty-tagged issues via GitHub API
gh search issues --label="bounty" --state=open --sort=updated
# Or use: label:"$", label:"prize:", is:issue, is:open

Platforms I hit consistently:

Platform	What they offer	Fee	Payout method
APort	Integration PRs ($5-$50)	0%	Stripe Connect
UnsafeLabs	Simple $1 tasks per PR	0%	Manual via GitHub
OWASP-BLT	Documentation & QA	0%	Manual
Algora	Wide variety ($5-$500)	Variable	Stripe Connect

Step 2: My Winning Formula — Small & Fast

Instead of chasing $500 tasks that take weeks, I focused on micro-bounties:

• 4 PRs on APort: $10 earned (Go Hello World integration + awesome list addition)
• 9 PRs on UnsafeLabs: $9 worth of $1/each tasks (SPF records, typo fixes, small code changes)
• 2 PRs on OWASP-BLT: $2 for simple deletion tasks
• 2 README typo fixes: ~$1 total
• 1 Codesphere template: FastAPI starter template

Total submitted: 17 PRs

Step 3: Let AI Do the Heavy Lifting

Here's the trick: AI agents are perfect for this workflow because bounty tasks share a pattern:

1. Read the issue description
2. Clone the repo
3. Understand the codebase structure
4. Make the change
5. Submit PR

With an AI agent, I can do steps 2-4 in minutes instead of hours:

hermes chat -q "Find and claim a $5 bounty on APort integrations repo"

The agent:

• Lists open issues
• Filters by bounty label
• Reads the codebase
• Implements the solution
• Opens the PR

Real Example: APort Go Hello World ($5)

The issue asked to add a "Hello World" integration in Go to the APort integrations repository. With Hermes Agent:

1. Fork the repo
2. Create a go/hello-world/ directory
3. Write main.go with the APort SDK integration
4. Add README with usage instructions
5. Submit PR

Total time: ~10 minutes. Payout: $5 via Stripe Connect (instant).

The Pipeline That Works

After 17 PRs, here's what I'd recommend for anyone starting:

1. Start with APort — their payment is reliable, clear criteria
2. Batch the $1 tasks — UnsafeLabs repetitive tasks add up fast
3. Use AI agents to auto-discover — set up a cron job to check for new bounties daily
4. Always /claim properly — some platforms need the exact syntax #issue-number
5. Track everything — notebook or spreadsheet with URLs, amounts, and status

Tools I Built

During this process, I created a search pipeline that automatically surfaces new bounty opportunities:

# Pseudocode for automated bounty hunting
repos = ["aporthq/aport-integrations", "UnsafeLabs/Bounty-Hunters"]
for repo in repos:
    issues = gh_api.search(f"repo:{repo} label:bounty is:open")
    for issue in issues:
        if is_claimable(issue):
            claim_and_work(issue)

What's Next

I'm scaling this up — adding more platforms, setting up automated workflows, and targeting $50-$100/month. The best part: AI agents make this accessible even if you're not a senior engineer.

Resources

• Hermes Agent — the AI agent I use
• APort — $5 starting bounties
• Opire — 0% fee bounty platform
• Algora — another good bounty platform

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Have you tried open source bounties? What's been your experience? Drop a comment below!