Architecture & design
Use AI to explore design options, highlight trade-offs, and generate documentation while validating decisions manually.
Methodology
We use AI not just as a coding assistant, but as a transformative way to approach the whole software development lifecycle. We apply it from the requirement stage, use advanced prompts to design architecture, infrastructure as code and CI/CD pipelines, before creating vertical slices of end-to-end features, accelerating agile sprints from weeks to days.
Four-phase process
1
Discovery
Clarify objectives, constraints, existing systems, and risks with stakeholders and teams.
2
Architecture
Define system boundaries, data flows, and integration patterns, balancing speed and maintainability.
3
Delivery & observability
Scaffolding, IaC, CI/CD pipelines, automated tests, monitoring, and deployment.
4
Implementation
End-to-end features vertical slices implementation: code, tests, and documentation, with reviews and pairing.
AI-augmented engineering practices
AI accelerates work but never replaces engineering judgment.
Code & refactoring
Generate scaffolding, suggest refactors, and keep code consistent across services, always reviewed by humans.
Testing
Generate tests from specifications and existing code to increase coverage without slowing down delivery.
Documentation
Keep architecture diagrams, ADRs, and API docs synchronised with the implementation.
Technical foundations
Microservices and APIs
Cloud-native infrastructure
Infrastructure as code
CI/CD and automated tests
Security and compliance
Observability and metrics
Working with teams
I collaborate with existing teams or act as the first technical hire. The approach is transparent and hands-on, with explicit knowledge transfer so you do not become dependent on a single individual.
- Pairing and design sessions with engineers.
- Architecture and code reviews.
- Short training modules on AI-augmented development.
- Pragmatic process improvements, not heavy frameworks.
Risk & quality management
Security & compliance
Apply secure design, threat modeling, and compliance-aware practices from fintech and payments projects.
Testing & automation
Build automated tests and pipelines to reduce regressions and manual overhead.
Observability
Implement logging, metrics, and alerts so issues are visible early rather than discovered by users.
Apply this methodology to your product
We can start with a short architecture or delivery review before committing to a larger engagement.