Case Study - AI-Native Delivery of User-Facing Software with Enterprise Full-Stack Foundations

Context

The delivery objective was to pair enterprise engineering discipline with AI-native iteration speed, without sacrificing product quality or user adoption.

Detailed description

A common challenge in digital services is not only building a working app, but shipping an experience that real users adopt while maintaining speed of iteration. In this case, we combined enterprise full-stack delivery experience with AI-native development workflows to ship multiple user-facing products and demonstrate adoption in real usage.

On the enterprise engineering side, we delivered modern full-stack web development work in a DACH delivery context as a Technical Architecture Specialist at Accenture DACH, using contemporary React and Next.js tooling as part of an engineering hub focused on building cool and useful software.

On the AI-native speed side, we intentionally stress-tested a new delivery mode: building a hosted, multiplayer-enabled 3D driving simulator over a weekend without keyboard input, creating prompts via voice transcription in Cursor and using Claude and other LLMs for code generation and iteration. The shipped result included multiplayer via websockets and approximately 2.5k lines of generated code.

We then applied the same ship-and-iterate pattern to productivity tools with direct user value:

• A Chrome extension that adds custom shortcuts to TradingView for experienced analysts and traders.
• A browser extension that adds thread indexing and total counts within the native UI for long-form social posting workflows.

These shipped products matter in public-sector positioning because they demonstrate end-to-end delivery mechanics: identifying a concrete user pain point, shipping an interface that lives inside an existing workflow (via extensions), and proving ongoing usage rather than stopping at a prototype.

This delivery orientation is consistent with deeper operational and leadership experience: leading and scaling a team (8-11 students) as President and CEO of ETH juniors, streamlining processes, and overseeing multiple client projects to completion; and long-running operational responsibility as COO in a biotech, pharma, and diagnostics manufacturing and distribution organization.

What this demonstrates for Swiss public-sector tenders: we can combine enterprise-grade web delivery experience with AI-native acceleration to deliver usable software quickly, while still grounding success in user adoption and repeatable delivery practices (team leadership, process improvement, and execution across business and technical constraints).

What we delivered

Delivery approach

We used a ship-and-iterate pattern: identify a concrete user pain point, deliver software directly inside existing workflows, and validate value through ongoing usage rather than stopping at prototype stage.

Outcome

The result was repeatable product delivery across business and technical constraints, with evidence of real adoption and faster iteration cycles.