As AI-powered coding tools surge in popularity, enterprises including security service providers are facing an unexpected challenge: more speed, but not necessarily more control.
OutSystems is aiming to address that gap with the launch of Agentic Systems Engineering a new approach designed to bring governance, structure and reliability to AI-driven software development.
The announcement reflects a broader shift in the industry, where organisations are moving beyond experimentation with AI and focusing on how to operationalise it at scale.
The Problem With Today’s AI Development Boom
AI agents can now generate code faster than ever, but this rapid acceleration has introduced new complexities.
Enterprises are dealing with fragmented tooling, inconsistent architectures and legacy systems that are difficult to integrate with modern AI workflows. Without proper oversight, this can lead to technical debt, security vulnerabilities and compliance risks.
OutSystems argues that solving this problem requires more than better tools it requires a fundamentally different approach.
Enterprise Context as the Missing Layer
Central to the company’s strategy is the Enterprise Context Graph, which acts as a shared intelligence layer across applications, data and workflows.
By giving AI agents a comprehensive understanding of enterprise systems and their interdependencies, the platform enables more accurate decision-making and reduces the risk of errors or misalignment.
This context-driven model is designed to ensure that all AI-generated outputs operate within defined guardrails, helping organisations maintain control even as development becomes more automated.
From Developers to Architects
The next-generation Mentor tool builds on this foundation by embedding AI capabilities directly into the development process.
With conversational interfaces and in-IDE support, Mentor allows teams to generate applications, analyse codebases and resolve issues more efficiently. It also automates repetitive development tasks, enabling teams to focus on higher-value activities such as system design and business logic.
The result is a shift in the developer role from writing code to orchestrating and validating AI-generated systems.
Balancing Flexibility With Control
Unlike closed ecosystems, OutSystems is positioning its platform as an open environment where multiple AI tools can coexist.
Developers can integrate third-party solutions like OpenAI Codex or Cursor while still operating within a governed framework.
This balance between flexibility and control is becoming increasingly important as enterprises adopt AI across multiple teams and use cases.
Real-World Use Cases Highlight Impact
Early adopters are already demonstrating the potential of the approach.
Manufacturing firm AllianceCorp Manufacturing is exploring the platform to build AI-driven workflows for extracting data from CAD drawings, while SRS Distribution has significantly reduced development timelines using Mentor’s automation capabilities.
These use cases point to a future where AI doesn’t just accelerate development it reshapes how enterprise systems are designed, governed and maintained.
As organisations continue to scale AI initiatives, the challenge will not be access to tools, but the ability to use them effectively within complex, regulated environments. OutSystems’ Agentic Systems Engineering is a direct response to that challenge, signalling a move towards more disciplined and context-aware AI development.
