Building useful software across AI, mobile, research and product systems

I work across the full arc of product engineering: discovery, architecture, implementation, delivery, and iteration. The common thread is making complicated ideas usable for real people.

Explore the work See university platforms

Anthony Humphreys

Product-minded senior developer

interface Founder extends SeniorDev {
  range: 'idea to shipped system';
  edge: 'product sense + delivery';
}

const anthony: Founder = {
  builds: ['AI', 'mobile', 'cloud'],
  leads: 'discovery to delivery',
  brings: 'clarity to complex work',
  bias: 'make the useful thing real'
};

Range

AI, mobile, web, cloud

Mode

Discovery to shipped product

Product engineeringAI systemsMobile platformsResearch translationService designCloud delivery

Capabilities with receipts

The work spans student services, AI assistants, public research platforms, internal tools, subscription products, and the unglamorous engineering that keeps them usable after launch.

Student-facing mobile platforms

Modernising iLancaster with React Native, Expo, faster check-in flows, safety features, digital passes, and data-informed iteration.

Applied AI that has to behave

Building tools like LUCA that support real student workflows: CV review, interview practice, job description analysis, and progress tracking.

Research and innovation delivery

Turning academic and partner ideas into usable products: maps, public platforms, data tools, admin systems, and prototypes.

End-to-end product ownership

Taking ideas from discovery and workshops through architecture, implementation, deployment, feedback, and maintenance.

Products and experiments

Lexio is where I ship focused software: small products, AI workflows, developer tools, and prototypes that flex my developer skills and keep my brain sharp.

Product studio

Lexio

A home for subscription apps and bespoke builds: products for developers, creators, internal tools, prototypes, and integrations.

AI product

GMprentice

A sandbox for tabletop GMs to practise with AI adventurers: party generation, character voice, dice, initiative, secrets, and session flow.

Personal workflow tool

JobMatch AI

An AI-powered job board that parses a CV, learns preferences, searches for relevant roles, and improves from user feedback.

University platforms and research translation

A lot of the interesting work happens between disciplines: careers, mobile services, sustainability, physics, public science, research visibility, and practical AI.

Careers AI assistant

LUCA

A Lancaster University careers pilot for independent employability practice: CV and cover letter review, interview modes, feedback reports, and LinkedIn recommendations.

Mobile platform

iLancaster

A daily companion for campus life, evolved through co-production and data: Expo migration, performance work, check-in improvements, digital passes, safety tooling, and support visibility.

Research interface

IceHunter front-end

A map interface for iceberg detection research, turning satellite radar and AI outputs into accessible location data for potential maritime use.

Research-to-product

Sustainable packaging tool

A web tool helping eCommerce businesses make data-driven packaging decisions that balance cost, compliance, and environmental impact.

Public science platform

AuroraWatch UK refresh

A modernisation project for a public-facing aurora platform built around real-time and historical data, alerts, and wider access to science.

Research web platform

Prob_AI research hub

A public site for an EPSRC-funded AI research hub, built with Next.js, Mantine UI, AWS, university content integrations, and a lightweight admin workflow.

How I tend to work

Strong technical work is rarely just code. It is judgement, collaboration, trade-offs, communication, and enough taste to know when an abstraction has wandered into self-importance.

Start with the shape of the problem before picking the stack.
Design for the people who will actually use and maintain the thing.
Use AI where it expands capability, not where it decorates a demo.
Keep systems understandable enough that future teams can safely change them.
Prefer evidence from users, data, and delivery over theatre. Theatre has excellent lighting and terrible uptime.