IT Consulting Philip Claren
I'm Philip Claren — system & software architect, lead developer and AI transformation consultant. For more than 18 years I've been building, scaling and modernising business-critical platforms — and today I guide IT organisations towards using AI productively and responsibly.
“I translate ambiguous business requirements into clean, maintainable architecture — and lead engineering teams to deliver.”
From high-traffic eCommerce and SaaS marketplaces to enterprise energy systems: today my focus is guiding software organisations through their AI transformation — with AI-assisted engineering, agentic workflows and LLM-powered product capabilities. So teams ship faster and smarter, without sacrificing quality and governance.
Embedding AI-assisted engineering into your team: AI pair programming, automated code review and test generation, agentic & RAG workflows, LLM features in the product — including pragmatic governance: data privacy, human-in-the-loop review and evaluation of output quality.
Clean Architecture, Domain-Driven Design and event-driven architecture for systems that are allowed to grow. From architecture due diligence to target architecture to modernising legacy platforms.
Enabling teams instead of creating dependencies: mentoring through pair programming, documenting architectural decisions, raising engineering standards — and translating technical reality into actionable guidance for stakeholders and decision-makers.
No consulting ivory tower: I build alongside the team. TypeScript, C#/.NET, React, Vue 3, Node.js — from MVP to production-grade platform on Azure or AWS. End to end, integrated into your existing IT landscape.
Enterprise customer-service platform: migration of the C#/.NET backend to Clean Architecture, Vue 2-to-3 and TypeScript migration of the frontend — and introduction of LLM-based developer tooling into the team, measurably accelerating delivery while raising code quality. Including guardrails for safe, compliant LLM use in an enterprise energy context.
C#/.NET · Clean Architecture · Vue 3 · TypeScript · LLM/RAG · Azure
SaaS B2B eCommerce marketplace: architecture due diligence of an externally built product, hardening and optimising the platform for continued growth, mentoring the team and advising non-technical decision-makers.
Node.js · Next.js · NestJS · TypeScript · AWS · Pulumi · PostgreSQL · GraphQL
Group-wide eCommerce & unified backend programme: target architecture for all brands (EnBW, Yello, NaturEnergie+), platform evaluation (Commercetools, Spryker, Magento, Shopware), MVP built on Commercetools and Azure — through to integration into the existing IT landscape, including reusable SDKs and a customer-context-aware pricing engine.
C#/.NET Core · React · Node.js · TypeScript · Commercetools · Azure · AWS
Vue.js application for contract management on yello.de plus a chatbot integration for the support centre — an early move towards automated, self-service customer support.
Vue.js · JavaScript · Chatbot integration
Mobile rewrite: joined a newly formed Scrum team to rebuild the Shopgate mobile client in React — including architecture patterns and coaching the team on scalable React architecture.
React · JavaScript · Scrum
Enterprise eCommerce: maintained and refined the backend systems for Deutsche Telekom's eCommerce platforms (shop.telekom.de and smarthome.de).
Ruby on Rails · Enterprise eCommerce
From product concept and UX design to the production platform: prototype in Rails/Node.js + Angular, rewritten in Elixir/Phoenix (Erlang VM) with a React/Redux frontend.
Elixir · Phoenix · React · Redux · Node.js
Built and led the engineering organisation, lead developer of both flagship products. Introduced Scrum/XP, pair programming and CI — plus the architecture of a high-performance multi-tenant framework.
Ruby on Rails · PHP · MySQL · MongoDB · Linux
Freelancing for small businesses before that, 1999–2007: web design & development, IT infrastructure, custom software and tooling.
Using, building, and understanding large language models and AI agents
A three-part look at modern AI: Part I is practice-first — from simple chat interactions through reasoning models, tool use and autonomous agents to full agentic workflows using MCP, skills and RAG. Part II makes it concrete with runnable Python code and a self-built MCP server. Part III turns to the fundamentals — from the math behind perceptrons and feed-forward networks to the architectures powering modern language models.
Prompting Recipes for Everyday AI
Hands-on prompting recipes for everyday AI with ChatGPT, Claude & Gemini — from core techniques through the workday, image and video generation, to automation and the critical use of AI: spotting hallucinations and handling privacy. Provider-independent, with special menus for students, teachers, the self-employed, teams and developers.
Whether it's an architecture review, an AI strategy for your engineering team or a project that simply needs to get delivered — drop me a line.