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How RingCentral builds AI-native work from engineering to ops

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How RingCentral builds AI-native work from engineering to ops

With ChatGPT Work and Codex, RingCentral builds AI product features faster and centralizes operational intelligence.

With nearly three decades of innovation in business communications, RingCentral has grown into a global company generating more than $2.6 billion in annual revenue, with thousands of employees worldwide. Today, the company is extending its tradition of innovation by embracing AI-native ways of working. By giving every employee room to experiment with ChatGPT Work and Codex, RingCentral has ensured that anyone at the company, regardless of engineering experience, can build transformative products and infrastructure.

To encourage AI fluency across a global engineering organization, RingCentral’s Office of the CEO sponsored an AI-Native Challenge. Every participant was given ChatGPT Work and Codex, and asked to build a complete, end-to-end project—with no mandated workflow or other constraints.

More than a coding exercise, the challenge immersed employees in the full AI-native development lifecycle, from planning and implementation to testing, documentation, CI/CD, and iteration. Nearly every participant created a working repository, and thousands of employees, including non-technical staff and even executives, delivered functioning projects.

For RingCentral, the challenge is a working model of a broader strategy: using AI internally to build products faster for their customers. The company applies the same Codex-enabled approach to accelerate development of its own AI-powered product portfolio—RingCentral AI Receptionist (AIR), AI Virtual Assistant (AVA), and AI Conversation Expert (ACE)—shortening the distance between an idea and a shipped customer feature.

“The clearest lesson from the challenge was that AI-native development isn’t about replacing engineers—it’s about amplifying them.


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