
AI isn’t just a buzzword anymore—it’s actively changing how we build, debug, and test software.
Whether you are an engineer integrating LLMs into your app or a QA figuring out how to test unpredictable AI API responses, upskilling is no longer optional. But with so much noise out there, where should developers actually start?
There are 5 incredible resources available at no cost:
1. Microsoft’s "Generative AI for Beginners" : A hands-on curriculum teaching you how to build GenAI applications using Python and TypeScript.
🔗 github.com/microsoft/gene…
2. DeepLearning.AI : Short practical tutorials focused entirely on interacting with and testing LLMs via API calls.
🔗 deeplearning.ai/short-courses/
3. DAIR.AI Prompt Engineering Guide: A comprehensive framework for crafting precise prompts and evaluating AI outputs for consistent, testable results.
🔗 promptingguide.ai
4. Anthropic's Educational Courses: GitHub tutorials on constraining models, reducing hallucinations, and forcing strict JSON API responses.
🔗 github.com/anthropics/cou…
5. Hugging Face: A introduction to practically implementing open-source AI models without relying solely on paid APIs.
🔗 huggingface.co/learn
As you start building and testing new AI features, you will be making a massive amount of API calls. And debugging those requests is exactly where Requestly comes in to save you time. 💙
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