Applied AI Series - Beyond Vibe Coding with Harness Engineering and Evals
AI coding has evolved rapidly from code completion and chat-based assistants into autonomous agents capable of planning, implementing, testing, and iterating on software tasks for hours. As frontier models become increasingly capable, however, model intelligence alone is no longer enough to determine how useful an agent is in real-world software development. The surrounding agent harness (tools, environment, context, execution loop, verification, and feedback) is becoming just as important. This changes another part of the Software Development Life Cycle (SDLC): Quality Control and Evaluation. When generating code becomes fast and inexpensive, the difficult question is no longer only "Can the agent build it?". It becomes "How do we know what the agent built is correct?" This article explores the evolution from the frontier model race to harness engineering, why verification is becoming a bottleneck for autonomous software development, and how Eval-driven SDLC can help teams safely increase Agent autonomy.