Loop engineering: stop prompting, start looping

Loop engineering is presented as an approach to AI coding in which agents repeatedly generate code, run it against a real system, evaluate the result through a reliable pass/fail oracle, and revise until the oracle confirms correctness or an iteration limit is reached. Using an Open-Meteo forecast client as an example, the text shows how code can compile and return valid data while still violating an unstated requirement, such as returning Celsius rather than Fahrenheit. It proposes keeping a version-controlled Postman collection as an inaccessible oracle that tests live API responses, while a restricted subagent runs the collection and returns failure messages to the coding agent without exposing the test source. This separation is intended to prevent agents from merely tailoring code to visible assertions and instead lets concrete API behavior guide corrections. The discussion emphasizes that tools such as Postman or Claude Code are interchangeable components of a broader pattern whose effectiveness depends on explicit machine-verifiable requirements, defined iteration budgets, capability boundaries, and logged feedback, while acknowledging that subjective or untestable goals still require human judgment.

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