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How Endava is redesigning software delivery around AI agents
For developers building AI workflows, this case shows how enterprise teams are integrating LLMs as persistent, task-specific agents—not just one-shot tools—offering a blueprint for scaling AI in production environments.
What happened
According to OpenAI Blog, IT services firm Endava is restructuring its software delivery process around AI agents. The company is leveraging ChatGPT Enterprise and Codex to accelerate development, automate workflows, and foster an AI-native culture. Endava's approach involves embedding AI agents into every stage of the software lifecycle, from design to deployment. By using these tools, the firm aims to reduce manual coding, improve code quality, and speed up time-to-market. The initiative also includes training its workforce to collaborate with AI agents, effectively shifting from a traditional development model to one where human oversight and AI execution are tightly integrated. For builders of AI workflows, this represents a concrete example of how enterprises are operationalizing LLMs beyond simple chatbots—using them as autonomous contributors in complex software projects.
Key takeaways
- Endava is using ChatGPT Enterprise and Codex to embed AI agents across the software delivery lifecycle.
- The goal is to accelerate development, automate workflows, and build an AI-native culture.
- AI agents are involved in coding, testing, and deployment, with humans providing oversight.
- Endava is reskilling its engineers to work alongside AI, moving from manual code writing to AI collaboration.
Why it matters
For developers building AI workflows, this case shows how enterprise teams are integrating LLMs as persistent, task-specific agents—not just one-shot tools—offering a blueprint for scaling AI in production environments.
This is an original editorial digest by AI Workflow Pro. Full reporting at the source:
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