Featured case studyLotus
Lotus
Cars
Long‑running legacy platform engineering for Lotus Cars across vehicle configurators, model pages, pre‑owned sales, dealership tools, and launch marketing.
Technical Lead & Senior Software Engineer
Hands‑on engineering leadership for complex digital transformation programmes. I help product and engineering teams turn fragile legacy web estates into robust platforms that are faster and easier to maintain, scale, govern, and improve.
I'm John, an award‑winning software engineering specialist based in sunny rainy Brighton, UK.
I am an enthusiastic senior software engineer and technical leader with over twenty‑three years of hands‑on experience.
I help teams and clients design, build and improve websites, applications and web platforms, pairing architecture, delivery judgement and hands‑on TypeScript, React, HTML, and CSS.
My portfolio is diverse; I work with global clients, solving real-world problems, including:
- engaging businesses, politicians, academics, and world leaders to shape global agendas;
- leading the headless replatforming of a much loved chain of restaurants, modernising its UK & Ireland web estate;
- overseeing the digital rebranding of a chain of much‑loved high‑end department stores;
- ... and revamping the online presence of a local food truck so that their customers knew where to find them.
Featured Case Studies
- Featured case study
The World Economic
ForumSenior JavaScript developer delivering a React‑based rebuild of the World Economic Forum's online platforms, whilst also leading the introduction of new user features.
- Featured case study
John Lewis
& PartnersSenior developer in the Findability team, leading the digital implementation of the John Lewis & Partners rebrand alongside new feature development, user journey optimisation, and performance improvements.
How I Usually Help
Embedded Technical Leadership
Principal‑level support inside active delivery when architecture, standards, mentoring, documentation, ownership transfer, and implementation decisions need strengthening whilst the team keeps shipping.
Fractional Technical Leadership
Senior technical direction for organisations that need CTO‑style judgement across roadmap, suppliers, architecture, and release risk before a permanent leadership hire makes sense.
Next.js Platform Architecture
Define Next.js platform boundaries when domains, routes, tenants, brands, content ownership, data ownership, deployment models, or team responsibilities are making change unsafe.
Headless Architecture Consulting
Headless architecture advice before CMS, content model, preview, revalidation, metadata, schema, media, localisation, and editorial ownership decisions become expensive to reverse.
Next.js Platform Consulting
Senior platform assessment and technical direction for React and Next.js estates where routing, CMS, deployment, SEO, ownership, and delivery risk have become one problem.
Performance Optimisation and Core Web Vitals
Route‑level performance work for modern front ends where field data, Core Web Vitals, scripts, fonts, images, data loading, or templates are weakening important user journeys.
Previous Clients
John Lewis logo 
The BBC logo 
GOV.UK logo 
HSBC logo 
British Airways logo 
eBay logo 
Condé Nast Britain logo 
Nintendo logo 
Lotus Cars logo 
Team GB logo 
Marvel Comics logo 
London Philharmonic Orchestra logo 
Bosch (BSH Group) logo 
Volkswagen logo 
Cisco logo 
Activision logo 
London 2012 Olympics and Paralympics logo 
Microsoft logo 
Apple logo 
Gatsby logo 
Plex TV logo 
LEGO logo 
Selfridges logo 
The World Economic Forum logo 
Made by Many logo 
AND Digital logo 
IMG Licensing logo 
Disney logo 
Boohoo Group logo 
Debenhams.com logo 
The Rolling Stones logo 
Wreel Agency logo 
Polestar logo 
MOSCOT logo 
Virgin Atlantic logo 
American Express logo 
The Guide Dogs for the Blind Association logo 
Style.com logo 
Macmillan Education logo 
Zara logo 
Boeing logo 
Valtech logo 
McCann Manchester logo 
Warwick Acoustics logo 
Nando’s logo 
Virgin Active logo
Latest Articles
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The Talent Bar Paradox in Engineering Hiring. The Talent Bar Paradox in Engineering Hiring
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The Web is Becoming Machine‑Readable First. The Web is Becoming Machine‑Readable First
Machine‑readable websites need more than schema. They need stable pages, clean entities, useful metadata, feeds, APIs and content that survives extraction.
Converting Objects to Query Strings and Vice Versa. Converting Objects to Query Strings and Vice Versa
Converting objects to query strings is essential for handling URLs in JavaScript. Here, I explore encoding, parsing, and managing query parameters in Next.js.
The False Economy of Cheap Engineering. The False Economy of Cheap Engineering
Cheap engineering can shrink payroll, but it often increases rework, instability, contractor spend, supplier dependence, and total delivery cost later.
HTTP Cache Validation with ETag and Last‑Modified. HTTP Cache Validation with
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Production Observability for Next.js: Instrumentation, Logs, and Release Debugging. Production Observability for Next.js: Instrumentation, Logs, and Release Debugging
Approach production observability in Next.js with contextual logs, traces, release markers, client errors, cache signals, build visibility, and business data.
The False Economy of Cutting QA in the AI Delivery Era. The False Economy of Cutting QA in the AI Delivery Era
AI‑assisted delivery can increase throughput, but cutting QA, accessibility, SEO, security, and exploratory testing in response is a costly mistake.
Everyone Wants the Best Engineers. Fewer Companies Want to Pay for Them. Everyone Wants the Best Engineers. Fewer Companies Want to Pay for Them
Underpaying senior engineers can look efficient on payroll, but often costs more through weaker hiring, slower delivery, contractor spend, and retention risk.
Your Website Has a New Customer: The AI Agent. Your Website Has a New Customer: The AI Agent
AI agents are starting to research, compare and narrow buying choices. Websites need to serve autonomous evaluators before human visitors arrive.
AI Slop is a Symptom, Not the Disease. AI Slop is a Symptom, Not the Disease
AI slop is a symptom of weak incentives, not just weak tools. This article links generic output to shallow briefs, poor review, and volume‑led metrics.