From zero to deployed: AI architecture that lets founders ship

The Mission

(we chose to accept it)

Come in with purpose. Build something that compounds. Leave it better than you found it.

Wayne Marley and Rikky Singh came to Test Double with a clear product vision, a defined technical starting point, and one non-negotiable standard: speed could not come at the expense of scale. No throwaway work. It was the founding principle Traingent walked in with.

The engagement was designed the same way. Not open-ended staff augmentation, but a structured partnership with a deliberate arc: align on the foundation, build it together, teach along the way, and exit when the team could own it independently. Test Double would come back when Traingent hit a problem that warranted it. That was the deal, and both sides held to it.

Ride With Dave was already defined: a cycling coach with genuine personality, real domain depth, and SMS as a primary interaction channel from day one. Test Double's job was to stress-test the technical approach; sharpen the stack; stand-up the scaffolding and guardrails to allow for responsible, fast-paced AI-assisted development; and jump-start engineering activities by directly supporting the build-out of the integration architecture and data pipelines.

Need help with your project?

Get in touch with our team

The Fix

Engineer for the team that comes after, not just the sprint in front of you

From the beginning, the goal was to build a product and platform that Traingent could confidently evolve over time. Architectural decisions were evaluated through the lens of maintainability, operational readiness, and team ownership. That meant making intentional choices early, documenting the reasoning behind them, and embedding standards directly into the development process.

Great software

Architecture designed for longevity
Early architectural validation ensured the platform aligned with Traingent's preferred technology direction while remaining adaptable as requirements evolved.
Clear boundaries and shared understanding
A layered architecture, supported by automated enforcement and visual documentation, made it easier for contributors to understand where new functionality belonged and how different parts of the system interacted.
Domain-informed data foundation
Fitness device integrations and a domain-specific data pipeline enabled athlete activity data to be ingested, normalized, enriched, and processed reliably, with observability built in throughout the workflow.
AI coaching experience aligned to product vision
Traingent's concept for a distinctive coaching personality was brought to life through workflow orchestration and quality controls designed to maintain a consistent user experience.
Operational readiness from day one
Logging, monitoring, alerting, tracing, and health checks were implemented alongside product development, ensuring visibility and supportability as the platform grew.
Infrastructure built for repeatability
Infrastructure-as-code, automated deployments, security controls, and development workflows established a foundation that could be consistently deployed and maintained across environments.

Great teams

Collaborative evolution of the technical approach: Test Double and Traingent worked closely to validate assumptions, refine architectural decisions, and adapt the platform as new information emerged throughout development
Domain expertise shaping engineering decisions: Product and technical decisions were informed by a practical understanding of athlete training data, helping ensure the system reflected real-world use cases rather than abstract technical requirements
Architecture decisions as a shared language: Architecture Decision Records (ADRs) were introduced early to capture key decisions and their rationale, creating a durable knowledge base that became increasingly owned by the Traingent team
Continuous learning through operations: Production incidents and unexpected challenges were treated as opportunities to improve the platform, with retrospectives, action items, and process improvements incorporated into ongoing development
AI-assisted development practices: Project-specific documentation, engineering playbooks, and development automation helped accelerate onboarding, improve consistency, and reduce repetitive work across contributors
Built for shared ownership: Knowledge transfer was not treated as a final phase of the engagement. Documentation, processes, and architectural choices were designed from the outset to support long-term ownership by the Traingent team

CONSULTANTS

Tech & Techniques

41 ADRs documenting major technical decisions and their rationale
Living project context and AI-assisted development playbooks
Reusable AI-powered workflows for deployment, review, and operational tasks
Monitoring dashboards, structured logging, and alerting from day one
Infrastructure-as-code enabling repeatable, one-command deployments
A codebase where the folder structure teaches you the information flow

The Results

Deployed product, capable team, and architecture built to compound

Within three months, Ride With Dave was running in production with AI-powered coaching, fitness device integrations, multiple user interaction channels, operational safeguards, and monitoring. Just as importantly, the platform was designed to be understandable, maintainable, and approachable for future contributors.

Documented decisions, not just outcomes: Hundreds of commits and dozens of Architecture Decision Records captured not only what was built, but why key decisions were made
From concept to production: The core product vision was delivered on a production-ready foundation without relying on throwaway prototypes or temporary infrastructure
A platform ready for growth: Infrastructure automation, deployment workflows, security improvements, and operational tooling were introduced early, creating a foundation that could support future contributors and capabilities
Domain knowledge embedded in the product: Training and activity data were transformed into meaningful coaching context, enabling the product to provide more relevant and personalized guidance to athletes
Growing internal capability: Over the course of the engagement, Traingent team members progressed from contributing within established patterns to independently authoring architectural decisions and delivering platform-level enhancements—one of the strongest indicators of successful knowledge transfer and long-term sustainability

Download project PDF

Contact our team