Building effective AI agents requires understanding four core engineering concepts: Prompt, Context, Loop, and Harness. Prompt defines how we ask the agent; Context provides the information it needs; Loop manages iterative execution; and Harness ensures safe operation. This article explains each concept with practical examples, showing how they interconnect to form a robust agent workflow. For developers, mastering these pillars is essential for designing scalable and reliable AI agents. The framework is applicable across different LLM platforms and can guide architecture decisions. Understanding Loop Engineering, in particular, helps automate multi-step tasks without human intervention. This structured approach reduces complexity and improves agent performance in production environments.
A clear breakdown of four key engineering concepts for building AI agents: Prompt, Context, Loop, and Harness, with practical insights.