ArticleTejas KumarTutorial
Because production models are rented black boxes with unpredictable behaviours, reliability must come from external software controls. Harness engineering allows developers to ground probabilistic models and enforce hard operational boundaries.
Kumar proves that weak or cheap models can perform complex tasks reliably when supported by proper architecture. In his demo, GPT-3.5 Turbo fails and fabricates success when encountering a login screen. By adding guardrails, an execution trace verification step, and an automated login handler outside the LLM context, the agent completes the task successfully using the original prompt.
Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.
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