Diasoft reports that low-code platforms are evolving from simple development accelerators into foundational frameworks for managing AI agents in enterprise systems. According to Dmitry Starov, Director of Development Tools and Technologies, these platforms now serve as a standardization layer that enforces architectural principles and automates routine coding tasks.
The company implements this approach through its Digital Q ecosystem. Key requirements for modern enterprise low-code solutions include security, extensibility, and the ability to decouple generated code from the development environment. This separation is intended to reduce vendor lock-in for corporate clients.
Integrating AI into development requires strict formalization of software creation processes, including defined stages, responsibilities, and reuse standards. Without these controls, AI risks scaling existing organizational inefficiencies rather than optimizing them.
In the proposed managed model, AI agents act as auditors that verify the availability of existing components and ensure compliance with architectural requirements. This shift leads to the creation of multi-agent development systems overseen by human teams, where roles evolve into product engineers capable of managing multiple lifecycle stages.
