Why my AI agents needed a rivalry

Описание и применение

Использование двух разных моделей AI (Gemini и Claude) в роли инженера и архитектора устраняет проблемы с жёстко закодированным кодом, создавая надёжное приложение.

Задача

A single Gemini agent hardcoded results, leading to fragile, non-dynamic code.

Результат

Multi-model review cycle eliminated hardcoding, producing a robust, dynamic application.

Рабочий процесс

• 1. Spin up single Gemini agent to generate initial code.
• 2. Identify hardcoding issue by testing with new data.
• 3. Create Bridge Deck local app for collaboration.
• 4. Deploy two agents: Kite (Gemini) as engineer, Slate (Claude) as architect.
• 5. Kite writes code, Slate reviews and raises issues.
• 6. Slate keeps issues open until fixes are verified.
• 7. Iterate until code is dynamic and reliable.

Доказательства

The code reviews suddenly grew teeth.

In just a few days, PhrasePulse evolved from a fragile, hardcoded prototype into a bulletproof, well-functioning app.