DINISO is an engineering R&D and consulting practice exploring how Forward Deployed Engineering, Agentic AI and disciplined software engineering can turn business and domain problems into production systems—particularly where quality, security, traceability and maintainability matter.
DINISO combines close domain collaboration, senior software engineering and Agentic AI R&D. The goal is not simply to generate more code, but to solve the right problem and deliver software that remains understandable, testable and maintainable.
Work close to stakeholders and domain experts to understand ambiguous problems, model workflows, define requirements, prototype solutions, integrate with existing systems and move software toward production.
Design and build maintainable systems across C#/.NET, cloud-native architectures, APIs, distributed workflows, security, automated testing and production operations.
Explore how LLMs and specialized AI agents can participate in disciplined engineering workflows using explicit specifications, tools, evaluation and human oversight.
Apply engineering rigor where quality, security, traceability and lifecycle evidence matter, with particular interest in MedTech and other regulated environments.
Work with stakeholders and domain experts to understand goals, constraints, workflows and the real problem. Use Event Storming and DDD to make the domain explicit.
Turn intent into requirements, acceptance criteria, boundaries, interfaces and architectural decisions before implementation accelerates.
Test assumptions quickly, build working software and connect APIs, data, enterprise systems and existing workflows.
Verify functionality, security, maintainability and—where AI is involved—agent behavior. Keep human review and accountable production decisions explicit.
My background is in senior full-stack and cloud-native software engineering, primarily with C#/.NET, distributed systems, Azure, web applications and integration-heavy products. The recurring pattern has been moving between domain understanding, architecture, implementation, integration and production concerns rather than treating them as separate activities.
At Cortrium, I worked on medical-device software and SaaS capabilities around ECG workflows, external healthcare integrations and report delivery. That work brought software engineering into direct contact with interoperability, cybersecurity, clinical data and regulated development, while deepening my understanding of IEC 62304, ISO 13485, ISO 14971, EU MDR and related lifecycle concerns.
Earlier through DINISO, product work including uchop.com took an idea through domain discovery, Event Storming, DDD, roadmap definition, prototyping, collaboration with UX and content specialists, team formation and production launch. We did not call this Forward Deployed Engineering at the time, but the operating model was similar: stay close to the problem and remain involved through delivery.
Today, DINISO brings those lessons together and explores how Agentic AI can augment the same lifecycle — without losing the architecture, traceability, testing, security and human judgment that make production systems trustworthy.
Forward Deployed Engineering establishes what needs to be solved. Agentic AI can then augment parts of that lifecycle through specialized agents with explicit responsibilities, constraints and checkpoints — not one unconstrained code-generating assistant.
Capture stakeholder goals, workflows, constraints, risks and user value.
Turn validated intent into structured requirements and acceptance criteria.
Propose boundaries, interfaces, trade-offs and implementation guidance.
Generate or modify code within explicit architectural and domain constraints.
Run tests, static analysis, security checks and consistency reviews; produce evidence.
Review evidence, resolve ambiguity and retain accountable control over production.
DINISO documents experiments, architectures, prototypes and lessons learned at the intersection of Forward Deployed Engineering, Agentic AI and disciplined software engineering. It also serves as a professional reference for Senior/Lead Software Engineering, Forward Deployed Engineering, Agentic AI Engineering, cloud-native systems and regulated software development.