Error handling is one of the most important (but least talked about) skills for AI builders who aren’t traditional software developers. When your app relies on multiple APIs, LLMs, or external services, something will eventually go wrong. A good engineering mindset doesn’t try to avoid errors; it plans for them. In this article, we break down error handling in simple, practical terms designed specifically for no-code and low-code AI creators.
This article explores common deployment targets: local, on-premises, cloud (VMs and serverless), hybrid setups, and the role of containers. You’ll learn the benefits, limitations, and considerations for each, and discover Pre-prototype habits to plan your deployment strategy before writing a single line of code.
This article walks vibe coders through the essentials of Continuous Integration, Continuous Deployment, and deployment discipline. You’ll learn why version control, automated pipelines, environment parity, and safe deployment strategies are critical, and how to plan them before writing a single line of code.
AI coding assistants let you build working prototypes in minutes, but speed can hide serious performance risks. A prototype that works for one user on your laptop may fail when multiple users arrive, requests spike, or data grows. In this article, we explore load testing, stress testing, and capacity planning, showing vibe coders how to plan for performance before writing a single line of code.
AI coding assistants make it easy to build working prototypes fast, but fast doesn’t always mean stable. Without automated testing, even small changes can silently break your app. In this article, we look at the testing techniques that protect your prototype from unexpected failures: unit, integration, regression, property-based, and fuzz testing.
AI coding assistants make it easy to build prototypes that work almost instantly. But there is a hidden risk you need to plan for: prompt-injection. Prompt-injection happens when a user or external content can trick your AI into ignoring its instructions, revealing sensitive information, or performing unintended actions.
AI coding assistants have made it easier than ever to spin up a working prototype, but “working” doesn’t always mean “safe.” In this first article of the Engineering for Vibe Coders series, we look at the importance of Security-First Coding, a mindset that starts before you write your first line of code.
