Developer Builds AI-Powered Debugging Journal With Security-First Prompting on Cloud Run

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A developer participating in Google's Cloud Run AI Challenge built DevLog, a structured debugging journal for developers, instead of the prescribed mood-reflection journal. The project centered on configuring Google AI Studio with a security-first directive that required the AI to produce a threat model — covering input surfaces, memory, tool execution, and inter-system communication — before generating any code. Each new feature request triggered a threat summary table mapping risks to countermeasures, acting as a binding contract against insecure code proposals. The app uses two separate Gemini API calls: one for free-form conversational rubber-ducking and a second dedicated call to extract structured, schema-constrained JSON data about the bug being discussed. This dual-call architecture was a deliberate design choice to prevent fragile regex-parsing of mixed conversational and structured outputs.

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