Reliable by Design
Error handling, input validation, monitoring and recovery are designed with the feature, not retrofitted after the first incident. A system that fails should fail visibly and predictably.
Technology
This page is about engineering decisions rather than a list of frameworks. The tools change per project; these principles do not.
Engineering principles
Each of these has a cost. We accept that cost because the alternative usually surfaces later, in production, at a worse time.
Error handling, input validation, monitoring and recovery are designed with the feature, not retrofitted after the first incident. A system that fails should fail visibly and predictably.
Anything another system needs to reach is exposed through an explicit interface with a defined contract, so integrations do not depend on internal implementation details.
Secrets, authentication, authorisation and validation belong on the server. Client code is treated as public, and permissions are granted at the narrowest scope that works.
Fewer moving parts, conventional patterns and readable code. Complexity is added only when the problem requires it, because someone else will maintain this later.
Systems that matter operationally carry logging, analytics and health checks, so questions about behaviour and cost can be answered with data instead of assumptions.
Architecture
Defaults we start from. Deviating is fine when there is a reason, and the reason gets written down.
The site you are reading follows the same rules. Pages are pre-rendered static HTML served
from Cloudflare's edge network, so a page view involves no server-side rendering and no
database query. The only code that runs on request is the small set of API functions under
/api: a health check, the service catalogue, the contact endpoint and the payment endpoints
reserved for future use.
You can check the health endpoint yourself: /api/health.
Capability areas
The areas we work in day to day. Where something falls outside this scope, we say so rather than learning it at your expense.
Task-specific model use with validation, fallbacks and cost visibility.
Versioned HTTP interfaces, webhooks and authenticated service boundaries.
Scheduled and event-driven jobs with retries, logging and exception queues.
Normalisation, validation and transformation across structured and text data.
Serverless and edge deployment, environment separation, managed secrets.
Accessible, responsive interfaces with server-side validation throughout.
Connections between operational systems with explicit ownership of each field.
Operational reporting and measurement built on the same data the system uses.
If you already have software in place, an assessment is usually more useful than a rebuild. We can review the current implementation and tell you what is worth keeping.