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How Endava builds an agentic organization with Codex
This real-world example shows how to practically implement AI agents in software development, offering a blueprint for teams looking to accelerate delivery without sacrificing quality.
What happened
A blog post from OpenAI details how Endava, a global IT services company, uses Codex to accelerate software delivery. According to OpenAI, Endava has built an 'agentic organization' by deploying multiple Codex-powered agents that handle tasks from requirements analysis to code generation. The company reports that using these agents reduced requirements analysis from weeks to hours. Endava's approach involves creating specialized agents for different stages of development, which work together under human oversight. The post highlights how the team integrated Codex into their existing workflows, focusing on areas where AI could provide the most leverage, such as interpreting client needs and writing boilerplate code. For developers building AI workflows, this case study demonstrates a practical pattern: combining human domain expertise with AI agents can drastically cut time in software planning and development, without replacing human decision-making.
Key takeaways
- Endava uses OpenAI's Codex to create a multi-agent software development system.
- Requirements analysis time dropped from weeks to hours, per the OpenAI blog.
- The system involves specialized agents for different stages, supervised by humans.
- Integration focused on high-leverage tasks like interpreting requirements and generating code.
Why it matters
This real-world example shows how to practically implement AI agents in software development, offering a blueprint for teams looking to accelerate delivery without sacrificing quality.
This is an original editorial digest by AI Workflow Pro. Full reporting at the source:
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