Every project moves through the same seven stages.
We don't stop when the AI demo works. We continue until the product is engineered for real-world use.
Discover
Define what and why.
- Stakeholder and user interviews
- Technical/architecture audit of anything already built
- Defining success criteria and scope
- A written problem statement and scope
- Initial architecture direction
Heaviest at this stage: your context and constraints shape everything downstream.
Generate
Move fast with AI.
- AI-assisted prototyping of core flows
- Rapid iteration on UI/UX direction
- Technical spikes for the riskiest unknowns
- A working prototype or proof of concept
- A clearer picture of what's actually hard
Review and react to prototypes early, before architecture is locked in.
Engineer
Make it a real system.
- Architecture and data-model design
- Authentication, integrations, and core business logic
- Code review and engineering standards enforcement
- A production-shaped codebase
- Documented architecture decisions
Periodic check-ins; less day-to-day involvement than Discover or Generate.
Evaluate
Test it actually works.
- Automated test coverage (unit, integration, end-to-end)
- AI output evaluation where applicable
- Manual QA against real-world scenarios
- Test suite and evaluation results
- A prioritized list of known issues
Review of test results and edge cases that matter to your business.
Harden
Fix edge cases, risk.
- Security review and fixes
- Performance and reliability work
- Error handling, retries, and graceful degradation
- A system that fails safely, not silently
- Documented known limitations
Sign-off on risk tradeoffs where relevant to the business.
Deploy
Ship to real users.
- Production infrastructure setup
- Deployment pipeline and rollback plan
- Launch checklist and smoke testing
- A live, monitored production system
Go/no-go decision; coordination on launch timing.
Evolve
Monitor and improve.
- Monitoring and observability
- Bug fixes and reliability improvements
- New features and AI/model optimization as needs change
- A system that gets more reliable and capable over time, not one frozen at launch
Ongoing, at whatever cadence fits, from occasional check-ins to a standing engineering partnership. This is also where the AI Product Maintenance & Evolution offer picks up for clients who want us to stay on past launch.