Vibe Coding Engineering

Turn AI-generated code into production software

5 followers

Turn AI-generated code into production software

5 followers

A Korean-and-English field guide for controlling AI-proposed changes through planning, architecture, TDD, review, release gates, security, payment, delivery, and operations. Built from real work across C++/Qt, C++20, QML, React, SvelteKit, AWS, and production commerce systems. Includes free verified samples and paid PDF, EPUB, DOCX, checklist, templates, and team-license editions.

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Launch tags:Education•Developer Tools•Artificial Intelligence

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Vincent 4.0

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I wrote this after repeatedly seeing the same gap: AI can produce a plausible change quickly, but a product still needs observable requirements, architectural boundaries, tests, release evidence, secure payment, and customer delivery. The public sample repository shows the exact boundary between verifiable proof and paid artifacts. I would value feedback from builders using AI in real production systems.

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3mo ago

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3mo ago

What evidence do you require before shipping AI-generated code?

AI can produce a plausible change quickly, but shipping still requires evidence. My current minimum is: observable acceptance criteria, an explicit architecture boundary, a focused test that fails before the change, review of the actual diff, and release evidence from the production surface.

I am launching Vibe Coding Engineering on August 4 PT as a field guide to that workflow, based on real C++/Qt, QML, React, SvelteKit, AWS, payment, and delivery work.

Which gate catches the most AI-assisted coding failures for you and which gate do today s tools still skip?

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