Product engineering
Seven stages every product goes through with us, and the practices that keep each one predictable.
Plan
Agree the problem, the users and what success looks like before code is written.
Practice: Written scope, tickets with acceptance criteria
Architect
Choose the data model, services and boundaries the product will grow on.
Practice: API contracts in OpenAPI, data and access design
Develop
Build in small, reviewed changes on a typed codebase.
Practice: TypeScript end to end, code review on every change
Integrate
Connect payments, identity, messaging, AI providers and existing systems.
Practice: Queues and workers for anything slow or retried
Test
Unit, API and end-to-end suites run on every change, with manual passes before release.
Practice: Integration tests against real databases in containers
Release
Ship through automated pipelines to containerised infrastructure.
Practice: Helm releases via GitHub Actions, image scanning before deploy
Improve
Watch how the software behaves in production and feed it back into the plan.
Practice: Tracing, error monitoring and metrics
General patterns from the work, described without naming products or customers.
Multi-tenant SaaS platforms
One codebase serving many organisations, each with its own users, branding, roles and data boundaries.
AI-assisted workflows
Language-model features embedded in everyday screens: drafting, reviewing, summarising and answering from a product’s own data.
High-volume job pipelines
Ingestion, matching and processing that run through queues and workers, sized automatically to the load.
Admin and analytics dashboards
Staff-facing tools for managing accounts, campaigns and reporting on outcomes.
See the capabilities behind each stage. SaaS, AI, QA, integrations and cloud.
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