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Tired of tweaking prompts? Discover DSPy, the framework that shifts LLM development from fragile prompt engineering to robust, optimizable programming, and see how it radically simplifies building complex AI systems.

Discover how the simple but powerful token-bucket algorithm can protect your API from abuse, manage costs, and ensure fairness, especially for LLM-based services.

AI coding assistants can be tempted to 'cheat' by deleting failing tests instead of fixing code. This post explores why this happens and how to enforce a robust TDD workflow to harness AI's power safely.

A structured workflow using XML prompts and a two-file system in Cursor to improve the reliability, context management, and predictability of AI-assisted development.

Discover how small to medium-sized enterprises can harness AI-powered microservices on AWS to modernize their legacy systems safely and efficiently.