Nextworld, the AI-native enterprise platform for eliminating Shadow ERP™, announced the general availability of Agentic Development, a new capability addressing the widening gap in the market between AI-generated prototypes and production-ready enterprise systems. The new feature enables teams to describe operational problems in natural language and receive production-ready, governed enterprise software in return.
AI-powered app builders have made it faster than ever to generate a working prototype from a prompt, but the path from prototype to production remains unsolved for most organizations. Crucial business functions such as security, governance, compliance, integration, testing, and long-term maintainability still fall to the teams adopting these tools, and the resulting applications frequently operate outside IT oversight, creating new layers of ungoverned risk.
The industry is beginning to reckon with this reality. Recent research has surfaced significant security vulnerabilities in AI-generated code, and enterprise leaders across sectors have raised concerns about deploying AI-built applications that lack the governance controls their organizations require. The pattern is familiar: teams move fast, but the output doesn’t survive contact with production.
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As a result, Nextworld built Agentic Development to break the pattern.
A different architecture, not a faster prototype
Where most AI building tools assign a single agent to generate code from a prompt, Agentic Development deploys a coordinated team of AI agents that mirror a real software development team. Product Owner Agents translate business needs into formal specifications. Design and Development Agents build the application against those specs. Quality Assurance Agents generate and execute tests to verify the output meets requirements. The result is software that has been specified, built, and tested before it ever reaches a user.
“Most agentic development tools stop at the prototype. Nextworld’s Agentic Development covers the full software development lifecycle giving teams the ability to go from a natural language prompt to a governed, production-ready application in hours without creating shadow IT or putting the burden of security and compliance back on IT,” said Vito Solimene, co-founder and chief technology officer of Nextworld.
The agent architecture is only half the story. Underpinning how those agents interact with the platform at runtime is Nextworld’s Model Context Protocol (MCP) Server, and the way it’s built is what separates it from how most teams are implementing MCP today. Rather than relying on a fixed library of pre-built tool calls, an approach that hits hard limits as query complexity grows, Nextworld’s implementation uses Code Mode, which allows agents to write and execute logic dynamically at runtime inside a secure, sandboxed environment. Agents discover available platform primitives, compose the logic they need for a given task, and execute it server-side. Data never enters the large language model’s context window. Role-based access controls and audit logging apply automatically, because the sandbox operates under the same security model as the rest of the platform.
The architectural foundation is specification-driven development. Rather than treating generated code as the end product, Agentic Development captures user requirements in a formal, AI-readable specification that persists across the entire lifecycle. As the user iterates, the specification evolves, and the agents rebuild the application to match. The specification is the durable asset. The generated application is a commodity that can be recreated at any point without losing the intent behind it.
SOURCE: PRNewswire