How Cisco Saves 1,500+ Engineering Hours Monthly with OpenAI Codex

Cisco embedded OpenAI Codex into production engineering workflows, achieving 20% faster builds, 10-15x defect resolution throughput, and saving 1,500+ engineering hours per month.

Impact

1,500+

Engineering Hours Saved Monthly

~20%

Build Time Reduction

10-15x increase

Defect Resolution Throughput

Weeks to days

Framework Migration Speed

Challenge

Needed to integrate AI into complex, mission-critical software systems with stringent security, compliance, and governance requirements.

Solution

Embedded OpenAI Codex into production pipelines for multi-repository systems, C/C++ codebases, and autonomous compile-test-fix loops.

Tools & Technologies

What Leaders Say

The biggest gains came when we stopped thinking about Codex as a tool and started treating it as part of the team.

Ryan Brady, Principal Engineer, Cisco Splunk Group
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Full Story

Cisco needed to integrate advanced AI capabilities into complex, mission-critical software systems operating in demanding production environments with stringent security, compliance, and governance requirements.

Cisco integrated OpenAI Codex directly into production engineering workflows, embedding it into existing development pipelines to handle multi-repository systems, C/C++-heavy codebases, and autonomous compile-test-fix loops.

The results: approximately 20% reduction in build times, 1,500+ engineering hours saved per month across global environments, 10-15x increase in defect resolution throughput, and framework migrations compressed from weeks to days.

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