Paydirt: How I Built an Open-Weight AI Agent to Turn GitHub Bounties into a Real Side Hustle

Описание и применение

Paydirt превращает поиск открытых бенчмарков в основанную на данных работу, используя локальные модели Gemma 3 и TabPFN для оценки вероятности выплаты и сопоставления навыков, а также Durable Workflows Temporal для отслеживания жизненного цикла.

Задача

Over 60% of open-source bounties never pay out, leaving contributors with uncompensated labor.

Результат

Paydirt turns bounty hunting into a data-driven side hustle, reducing ghosted issues and enabling contributors to earn by focusing on high-probability payouts.

Рабочий процесс

• Discover funded issues by scraping and normalizing bounties across GitHub
• Predict payout probability using TabPFN Bayesian model on 8 tabular features
• Calculate expected value and rank opportunities by hourly earning efficiency
• Match contributor skills locally with Gemma 3 embeddings via Ollama
• Track bounty lifecycle with Temporal workflows and durable timers
• Submit PRs and release bounties with manual confirmation and safety guards

Доказательства

Over 60% of open-source bounties never pay out, turning developer side-hustle time into uncompensated labor.

Источник

Paydirt turns open-source bounty hunting from a lottery into an evidence-based side hustle.

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Uses Prior Labs' TabPFN Bayesian tabular foundation model to score whether a funded issue will actually merge and pay out based on repo velocity, maintainer response intervals, review churn, and bounty size.

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Local Skill Matching via Gemma: Embeds your local git commit history and GitHub profile via open-weight Gemma 3 + EmbeddingGemma running entirely on your machine through Ollama.

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