☁️ Cloud & Databases

One Dev's Mad Experiment: Building aeoptimize by Dispatching Claude, Gemini, and Copilot in Parallel

Imagine ditching the endless back-and-forth with one AI. This dev built a slick CLI by firing off tasks to three AIs at once — and the results? Faster code, caught vulnerabilities, better tools for everyone scraping for AI attention.

CLI terminal output showing aeoptimize scoring a website with multi-AI insights

⚡ Key Takeaways

  • Multi-AI workflows split tasks by model strengths for faster, higher-quality code. 𝕏
  • aeoptimize CLI audits sites for AI readability with rules + optional AI consensus. 𝕏
  • Parallel AIs act as adversarial reviewers, exposing dev blind spots like SSRF vulnerabilities. 𝕏
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Originally reported by Dev.to

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