Platform Ecosystem

Inside the Six Disciplines That Build Every Platform

MyNew Technologies builds and operates an integrated ecosystem of platforms — commerce, learning, and cybersecurity — on one engineering foundation. This is the technical anatomy of that foundation: the six disciplines, the stacks behind them, and the patterns we build by.

System Architecture

Every platform starts at the whiteboard, not the IDE. We define the domain model, service boundaries, and API contracts before a line of code is written — so the system has a shape that can absorb change instead of fighting it.

We work in bounded contexts: each subsystem owns its data, exposes a versioned contract, and fails in isolation. Synchronous calls are minimized in favor of event-driven choreography, so a slow dependency degrades gracefully rather than cascading.

Architecture decisions are captured as ADRs and the topology is documented as diagrams-as-code — the design stays legible to the next engineer, and to the AI tooling that will read it later.

Architecture Stack

Domain-driven design · C4 model diagrams · OpenAPI contracts · Event-driven messaging

Key Patterns

Bounded contexts · CQRS where it earns its place · Idempotent consumers · Versioned APIs

Engineering Stack

React + Vite · Node.js / Express · Python · PHP · TypeScript

Delivery Practices

Trunk-based CI · Unit + integration tests · Code review on every PR · Diagrams-as-code

Full-Stack Development

Production code across the entire stack — typed, tested, and reviewed. React and Vite on the front end; Node.js, Python, and PHP on the back end; everything behind a CI pipeline that will not let a red build reach main.

Front ends are component-driven and accessibility-checked, with state kept explicit and side effects isolated. Back ends expose clean REST or GraphQL surfaces, validated at the boundary and instrumented for tracing.

We treat maintainability as a first-class requirement: clear module boundaries, meaningful test coverage, and documentation that lives beside the code — so the platform is still tractable a year later.

AI & Automation

AI is designed in as infrastructure, not bolted on as a feature. We integrate LLMs, ML pipelines, and intelligent agents directly into the systems we build — with the data models and event surfaces that make those integrations clean.

LLM work ships with the unglamorous parts handled: prompt versioning, context-window budgeting, structured-output validation, evaluation harnesses, and fallbacks for when a model call fails or drifts.

Automation pipelines are event-triggered and observable end to end. Every system we design is assessed for AI-readiness — clean schemas and well-defined APIs are what make future intelligence integrate without a re-architecture.

AI Stack

Anthropic / Claude API · LLM + ML pipelines · Intelligent agents · Structured-output validation

Integration Practices

Prompt versioning · Context management · Eval harnesses · Graceful fallbacks

Commerce Stack

Magento 2 / Adobe Commerce · EDI document flows · B2B punchout catalogs · ERP & payment integration

Operational Practices

Staging-verified releases · Index & cache strategy · Core Web Vitals budgets · Anti-corruption layers

Magento & eCommerce

Enterprise commerce engineering — Magento 2 at its core, extended with EDI document flows, B2B punchout catalogs, and custom integration layers built against documented contracts rather than brittle direct coupling.

We treat the storefront as a system: catalog architecture, indexer and cache strategy, Core Web Vitals budgets, and a staging mirror where every upgrade and patch is verified before it touches production.

ERP, payment, and fulfillment integrations are isolated behind an anti-corruption layer, so a third-party API change is a contained edit — not a store-wide incident.

Cloud & DevOps

The infrastructure your platform runs on, designed and operated with the same rigor as the application. AlmaLinux, Nginx, and PM2 under a CI/CD pipeline that makes deployment a non-event.

Releases flow through GitHub Actions: build, test, and deploy stages gated so nothing ships unverified. Configuration is codified, environments are reproducible, and rollbacks are a single action.

Every environment carries monitoring, alerting, and an incident path from day one. Infrastructure is sized to scale horizontally — elastic where load demands it, never a hidden bottleneck.

Infrastructure Stack

AlmaLinux · Nginx · PM2 · Firebase · GitHub Actions CI/CD

Operational Practices

Codified configuration · Reproducible environments · Monitoring & alerting · One-action rollback

Security Stack

Threat modeling · Zero-trust design · Encrypted data paths · AKLupX adaptive firewall

Key Practices

Least-privilege access · Managed secrets · Contained blast radius · Behavioral monitoring

Security by Design

Security is a design discipline, not a final-stage audit. Threat modeling, least-privilege access, and encrypted data paths are part of the architecture from the first diagram — reinforced by AI-powered monitoring through AKLupX.

We design toward zero-trust: every service authenticates, every boundary validates, secrets are managed rather than committed, and the blast radius of any single compromise is deliberately small.

AKLupX, our kernel-level adaptive firewall, adds a live layer — behavioral threat detection and autonomous response — so protection keeps pace with threats instead of trailing them.

Build on This Foundation

Have a Platform That Needs This Kind of Engineering?

Whether you are modernizing a legacy stack, launching a new platform, or integrating AI into production systems — these six disciplines are how we approach the work. Let us map your architecture together.

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