We’ve reimplemented our blog’s related article recommendation system using modern artificial intelligence techniques. The system is cheaper, more performant, and produces better results.
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How discovery work differs for an AI product, including tips on how to turn your AI product from good to exceptional.
Learn how AI streamlined the product design sprint process for a crowdfunded events platform, from idea generation to user testing. It highlights the strengths of AI-assisted design and identifies areas for improvement.
Transitioning the codebase from using environment variables to Rails Credentials for Zero-Downtime Deploys.
Early in the product lifecycle, there’s no one better placed to gather data for business decisions than a developer. Here are some examples of what (and how) Rails developers can contribute with “hacky answers”.
Think AI can’t be ethical? Think again! Check out the cheat code for creating innovative, user-trusting, privacy-first products. Ready to try the ®REPEATS method? 🔍💻
Tests provide value beyond verifying behavior and catching bugs. Reading, writing, and interacting with tests empower developers to observe – and therefore gain knowledge about – their complex codebase.
Gender is not a binary, and a binary is not a boolean.