10 years ago, we presented the philosophy of the CUBA Platform. Back then, the situation in Java development was very different. There was a broad variety of frameworks and tools in the Java SE world, without any clear mainstream technological leader. Five years ago, we identified Spring Boot as the winner of the Java technological race and invested development efforts in making it the platform’s core. This was how Jmix came into life, replacing the CUBA Platform. In the Jmix introduction article, we emphasized gaining a better developer experience, alignment with the most popular Java techs to date, making Jmix apps smaller, and maximizing application development productivity.
Nowadays, we recognize how modern AI development tools are transforming the industry, disrupting what we used to call “development productivity”. Since the beginning of 2025, the Jmix team has conducted in-depth R&D to understand how Jmix can continue to bring value in the AI era. This document reflects the key findings of our research and highlights the engineering priorities of the Jmix team in adopting AI in the future.
Engineering is the Core Competence
Generative AI has already become an integral part of our lives, transforming the way software is developed. In our view of the current state of the art, we share the perspective of Martin Fowler - one of the most influential figures in enterprise software development. While the current results are indeed impressive and promising, significant issues related to the use of large language models (LLMs) remain that cannot be ignored. AI amplifies both productivity and fragility. Saving time on design and launch comes at the cost of heavier, more fragile systems that require more hardware and cost more to maintain.
Software engineering, once largely deterministic, is now entering an era of tolerance margins and variability - much like civil or process engineering. The question is no longer “Can AI write code?” but rather “How do we ensure that code is safe, maintainable, and enterprise-grade?”.
At Jmix, we embrace an engineering mindset - leveraging the best of AI to make rational, well-informed decisions throughout the software development process.
Reliability is the Core Principle
In the AI era, Jmix is not just a high-productivity application development platform. It is the battle-proven architecture of how enterprise Java back-office systems should be built and maintained. With more than 10 years of successful implementation of Jmix as the foundation for multiple enterprise projects across various industries, it has proven to be a sustainable horizontal development technology.
As AI amplifies both productivity and fragility, Jmix’s core values in the AI era can be defined as the following:
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Predictable – Guardrails against AI chaos
Jmix applications follow a battle-proven architecture, ensuring that every component behaves as expected—no surprises at runtime, regardless of whether the code is written by humans or AI. -
Interoperable – Built to integrate, not isolate
Developers integrate Jmix with enterprise systems, frameworks, and corporate LLMs. Jmix doesn’t replace your stack. It anchors it. -
Consistent - Unified by design
Jmix enforces clear conventions and structure so that multiple developers and AIs can collaborate without drifting in style or approach. -
Guarded - Secure and governed by default
From role-based access to server-side rendering, Jmix reduces the attack surface that AI-generated glue code might expand. -
Sustainable – Built for the long run
Applications developed on Jmix age gracefully. Unlike prototype-driven projects that degrade over time, Jmix preserves long-term maintainability and reduces operational and technical debt.
The reliability of the technological stack within Jmix remains a key priority for us.
Where We Invest in AI - and Where We Don’t
Some development platforms rush to retrofit their IDEs with drag-and-drop UI builders for “AI productivity”. We see little value in doing this for Jmix Studio.
Why? Because modern AI code agents already acquire deep context directly from a structured Jmix project. They don’t need Studio to imitate low-code tools that offer no real value. Jmix’s conventions are structured so AI tools can easily understand them.
Instead, we focus our future engineering efforts on AI features for the end-users of Jmix applications, providing them with a dynamic and flexible workspace:
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Text-to-UI builder. A personalized UI-design builder integrated into the Jmix app that enables end-users to prompt for the requirements and customize the UI at runtime. The changes will be implemented instantly.
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Zero-UI assistant. A chat-based UI component embedded into the Jmix app eliminates the need to surf across disparate views to get the needed data or run some business logic. This should be a streamlined, straightforward, all-in-one enterprise tool.
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Text-to-Report builder. A new AI-powered wizard enables users to create reports using natural language descriptions. Users can now gain data insights while adhering to security constraints, without requiring additional involvement from system administrators.
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AI-assisted BPM modeling tool. Corporate AI agents can now act as digital coworkers within workflows, orchestrating tasks across humans, systems, and external AI services. They seamlessly integrate external data sources (APIs, corporate data lakes, knowledge bases) into processes without manual customization.
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Jmix-based tools for AI-agents. Modern back-office apps don’t live in isolation. They must be accessible through Microsoft Teams, email, corporate messengers, or portals - wherever employees spend their time. Jmix aims to make this integration effortless and low-code-free, even by exposing Jmix apps as MCP servers so they can talk directly with corporate AI agents.
All together, this makes us prioritize developing dynamic tools at app runtime, which will allow end-users to customize Jmix apps more easily and quickly. We believe that combining AI-assisted runtime tools with the robust Jmix enterprise architecture will make a giant leap in back-office automation.
Conclusion
The next era of enterprise software won’t be about “faster CRUD” - AI has already trivialized that. It will be about:
- Preventing expertise recession.
- Embedding guardrails so AI doesn’t collapse enterprise IT into Shadow IT.
- Empowering employees with smarter enterprise applications, without burdening developers with fragile prototypes or endless customizations.
Jmix is the platform that keeps enterprise development on the rails in the AI age.