Six Months of AI-Assisted Software Development: A Critical Evaluation of Vibe Coding, Agentic IDEs, and Real Engineering
Introduction
For roughly the past six months, I have been working intensively with large language models, agentic IDEs, and AI-assisted coding tools. During this process, I researched new quantization algorithms for large language models, worked on an algorithm I called SeaTree, developed a programming language named HudHud Script, and experimented with different models across many domains including algorithm design, programming language development, virtual machine architecture, benchmarking, profiling, refactoring, deployment, translation, localization, and systems architecture.
This text is not an attack on artificial intelligence. On the contrary, I believe AI is an extremely powerful tool. However, what I observed over the last six months is this: when used correctly, AI can dramatically increase a developer’s productivity; but when you hand over the entire process to it, you can easily end up surrounded by technical debt, fake success metrics, misleading benchmarks, security risks, fake/stub/placeholder code, unnecessary fallback mechanisms, and fragile architectures.
