EconPulse

Case Study

Built in 48 Hours with AI

How a solo developer used Claude Code to ship a complete EdTech platform — and what it means for the future of software development.

The Story

EconPulse started with a simple observation: A-Level economics students are expected to reference real-world news in their exams, but most teenagers don't read the Financial Times. The gap between what examiners want and what students actually consume was obvious — and so was the solution.

We wanted to build a daily economics digest that takes real news, runs it through AI analysis, and maps it directly to exam board specifications. Every morning, students would receive a brief they could read in ten minutes that would make them the most informed person in their economics class.

The question wasn't whether this was a good idea. The question was whether a solo developer could build it — a full-stack application with authentication, payments, an AI pipeline, email delivery, and multi-board curriculum mapping — in a weekend.

The answer, it turns out, is yes. Using Claude Code as an AI pair-programming partner, the entire platform was architected, built, and deployed in roughly 48 hours. The stack: Next.js 15, React 19, Tailwind CSS 4, PostgreSQL via Neon, Stripe for payments, Resend for email, and Claude AI for the content analysis pipeline itself.

This is a case study in what happens when the economics of software development fundamentally change. When a single developer with AI tooling can produce work that previously required a team of five working for three months, the implications extend far beyond technology.

Development Timeline

From Idea to Launch

Day 1Morning

Project Inception

  • Core architecture and project scaffolding
  • Authentication system with Auth.js
  • Landing page and marketing site
  • Database schema with Drizzle ORM
Day 1Evening

The Intelligence Layer

  • AI pipeline: RSS ingestion to Claude analysis
  • AQA curriculum mapping (141 topics)
  • Email delivery system via Resend
  • Daily digest generation workflow
Day 2Morning

Content & Quality

  • Content quality pass and editorial tone
  • Thought pieces and deeper analysis
  • On-this-day historical economics features
  • GDPR compliance and cookie consent
Day 2Evening

Monetisation

  • Stripe integration and checkout flow
  • Pro tier with archive access
  • Content gating for free vs Pro users
  • Subscription management portal
Day 3All day

Scale & Launch

  • Multi-board support (6 UK exam boards)
  • Weekly deep-dive long-form content
  • Curriculum library and topic browser
  • Final QA, performance tuning, launch prep

By The Numbers

The Build in Numbers

48 hours

Total development time

~30

Total files created

6

UK exam boards supported

141

AQA curriculum topics mapped

20+

RSS news sources

£0

Infrastructure cost (free tier)

~£15,000

Estimated traditional dev cost equivalent

1

Developer

Technology

The Stack

Next.js 15Framework
React 19UI
Tailwind CSS 4Styling
ShadCN UIComponents
Drizzle ORMDatabase
Neon PostgreSQLData
Auth.jsAuthentication
ResendEmail
Claude AIAnalysis
StripePayments
VercelHosting
Claude CodeDevelopment

What This Means

An Economic Analysis

For a platform that teaches economics, it seems only fitting to analyse the economics of how it was built.

Cost Disruption in Software Development

Traditional estimates for a platform like EconPulse — authentication, payments, AI pipeline, email system, multi-tenant content management — would place development costs at approximately £15,000 to £25,000 with a timeline of 8 to 12 weeks. The AI-assisted approach reduced this to effectively zero direct development cost (beyond the developer's time) in 48 hours. That's not a marginal improvement. It's a 10–50x reduction in the cost of production.

Implications for Solo Founders

The barrier to entry for software products has collapsed. A single developer with domain expertise and AI tooling can now build and ship products that previously required venture funding and a development team. This democratisation of capability means the constraint has shifted from “can you build it?” to “do you understand the problem well enough?” — a far more meritocratic filter.

The Economics of AI-Assisted Coding

What we're witnessing is a classic productivity shock. AI coding tools don't replace developers — they amplify them. A senior developer who understands architecture, security, and user experience can now execute at the speed previously reserved for large teams. The knowledge and judgement remain human; the implementation velocity is augmented.

Creative Destruction in the Development Industry

Schumpeter would recognise this pattern. The development industry is experiencing creative destruction: lower costs of production, faster iteration cycles, and a redistribution of value from labour-intensive implementation toward design thinking and domain expertise. The developers who thrive will be those who understand what to build and why, not just how.

Built By

Glooper

Glooper is a UK software development studio specialising in AI-augmented development. We build production applications at unprecedented speed using the latest AI tooling.

This case study is a living document, updated as EconPulse evolves. Last updated: February 2026.