Eclair
Éclair is an app designed to help foreign residents in France pass their civic exam for multi-year and permanent residency cards.
- AI agent design
- Prompt engineering
- Multi-agent orchestration
- Product management
✨ Overview
- Role
Product Manager & Automation Specialist
Discovery & Research, UX Architecture & Strategy, Rapid Prototyping & Testing, Brand Identity & UI Design
- Platform
Android
- Timeline
2026 – Current
- Status
In Development
- Deliverables
Design
User Flow, Wireframes, High-Fidelity Prototype, Design System, Branding, Visual Design, Logo
- Overview
-
Éclair: an AI-orchestrated product team. I designed and ran a team of seven specialist AI agents (product, UX/UI, architecture, backend, frontend, QA, DevOps) to take a civic-exam prep app from problem to build-ready plan.
Tools
Claude
MobbinFigma
✨ Context
Since January 2026, anyone in France applying for their first multi-year residence card (Carte de Séjour Pluriannuelle – CSP) or resident card (Carte de Résident – CR) must pass a mandatory 40-question civic exam. Failing the exam means retaking it and facing direct delays in securing legal residency status.
Balancing high-stakes exam preparation with everyday work, administrative duties, and family life creates immense stress. Candidates need an everyday app that gives quick access to the exact content they need, so they can study on the go: on the metro, or during any small pocket of free time.
Preparing for a critical exam shouldn't feel like a heavy, time-consuming burden on top of an already busy life. By providing direct, friction-free access to study materials on mobile devices, candidates can seamlessly integrate exam preparation into their daily routine.
✨ The Challenge
Problem Framing
Most existing resources for the French civic exam fail to provide a centralized and efficient learning experience. Applicants are given access to long lists of around 200 potential exam questions, but are left on their own to research, verify, and compile accurate answers.
Additionally, passively reading through hundreds of questions creates severe cognitive overload, making memorization difficult. There is a clear gap in the market for an intelligent, on-the-go tool that combines verified content with adaptive learning technology, turning studying into a structured, low-stress daily routine.
Pinpointing Issues
- Missing & Fragmented Answers: Official sources provide a large bank of 200 questions, but candidates have to spend valuable time hunting for verified, accurate answers across multiple platforms.
- Passive & Inefficient Memorization: Rote-reading massive lists of text is ineffective, leading to poor retention and high exam anxiety.
- One-Size-Fits-All Learning: Traditional methods force candidates to review questions they already know, wasting time rather than focusing on their personal weak spots.
- Lack of Progress Visibility: Candidates have no clear way to measure their readiness or know when they are truly prepared to score at least 32/40 on the official test.
- Rigid Study Demands: Existing materials require long, uninterrupted study sessions, making it hard for busy people to study during quick daily downtime.
✨ The Solution
Goals
The solution is an on-the-go study companion that combines verified exam material with intelligent micro-learning. It transforms the overwhelming 200-question pool into manageable, effortless daily prep where users can:
Solution Grid
Verified Answers
Access all ~200 official questions paired with clear, verified answers in one place.
Spaced Repetition
Master key facts for the long term using proven review intervals.
Adaptive Focus
Automatically concentrate on challenging questions based on individual performance.
On-the-Go Preparation
Fit bite-sized study sessions into daily commutes, metro rides, or quick breaks.
Readiness Tracking
Monitor real-time progress toward achieving the required 32/40 passing score.
Stress-Free Learning
Build true exam confidence without adding dedicated study hours to a busy schedule.
✨ Design Process
Approach: a product team made of AI agents
Instead of one general-purpose AI chat, I split the product lifecycle into phases and gave each phase a specialist agent:
- Product Manager: Problem analysis, competitor research, the full product spec.
- UX/UI Designer: The design system and screen-by-screen specs.
- System Architect: Tech stack, data model, security and delivery order.
- Backend & Frontend Engineers: Ready to build from the architecture’s interface specs.
- QA & Test Automation: A test plan focused on the failures that would cost user trust.
- DevOps & Deployment: Builds, app store releases and runbooks.
Plus a Field Researcher agent that collected real candidates’ experiences of the exam’s situation questions.
Every handoff is a document. The designer works from the product spec, the architect works from both, and the engineers work from all three. Because each agent builds on the previous agent’s work, every decision can be traced back to where it came from.
