The AI agent landscape is flooded with new engineering terms: Prompt Engineering, Context Engineering, Harness Engineering, and Loop Engineering. This post provides a clear taxonomy to understand how these concepts evolved from simple prompt crafting to complex loop-based agent architectures. For developers and tech leads, this framework is essential for designing scalable, autonomous agents. The shift from static prompts to dynamic loops represents a fundamental change in how we build AI systems. Understanding this progression helps teams choose the right engineering approach for their use cases, whether it's a simple chatbot or a multi-step reasoning agent. The post also highlights the importance of context management and harness design in production systems. This is not a tutorial but a conceptual map that can guide architectural decisions.
A structured breakdown of AI agent engineering concepts from Prompt to Loop, helping developers navigate the field.