2025 (old) & 2026 (new) · UX Lift

An AI-Native SaaS product I built e2e

Identified a gap in Berlin's design job market, validated it with 30+ designers, and shipped a working web app in 15 days in 2025. Now rebuilding it using newer technologies and removing AI slop.

Product

UX Lift, an AI native B2C SaaS product that gives junior designers real use cases to build portfolio work from and then connect to relevant startups.

Role

Founding Product Designer

Team

Solo (product strategy to production)

Timeline

Apr–Jun 2025 (old); Sept–Nov 2026 (new)

CONSTRAINT

Limited budget for backend implementation in 2025

WEB LINK

UX Lift.app

Outcome

2025: 30+ designer interviews · 100+ early subscribers · Shipped in 15 days

2026: Launching in November

Product

UX Lift, an AI native B2C SaaS product that gives junior designers real use cases to build portfolio work from and send custom made proposals to relevant startups.

Role

Founding Product Designer

Team

Solo (product strategy to production)

Timeline

Apr–Jun 2025

CONSTRAINT

Limited budget for backend implementation

WEB LINK

UX Lift.app

The situation

I was attending design community events in Berlin and meeting designers at every stage of their career. A pattern kept coming up in conversations, in job boards, & in my own job applications.

Around 90% of product design roles in Berlin required 5+ years of experience. Junior designers were stuck in a loop: they couldn't get hired without shipped work, and couldn't get shipped work without being hired. Bootcamp projects and unsolicited redesigns weren't cutting it. Hiring managers wanted to see real problems solved for real users.

Understanding the problem

Key decisions

Validate before building

I spoke with over 30+ junior designers and some mid & senior- level too to understand whether this problem was widespread enough to build for. Three needs kept surfacing:

Find credible problems

Designers could find fictional prompts and redesign exercises, but nothing grounded in real user behaviour and business context.

Know what makes work strong

After finishing a project, designers weren't sure if their work demonstrated the product thinking hiring teams look for.

Connect work to opportunities

Creating another case study had limited value if designers still had to search separately for relevant companies.

Find credible problems

Designers could find fictional prompts and redesign exercises, but nothing grounded in real user behaviour and business context.

Know what makes work strong

After finishing a project, designers weren't sure if their work demonstrated the product thinking hiring teams look for.

Connect work to opportunities

Creating another case study had limited value if designers still had to search separately for relevant companies.

Understanding Product Strategy

I researched to pressure-test the product-market fit question and potential value proposition before committing to a build.

Understanding different aspects of the project

I analysed these questions before I started the project.

Are you the right person to solve this?

How big is the market?

How acute is this problem?

Did this recently become necessary?

Do you have competition?

Do users want it or not?

Idea you want to work for years

Are there good proxies for the business?

Is this scalable business?

Are you the right person to solve this?

How big is the market?

How acute is this problem?

Did this recently become necessary?

Do you have competition?

Do users want it or not?

Idea you want to work for years

Are there good proxies for the business?

Is this scalable business?

Identifying the core problem

The JBTD research surfaced a clear job map: designers needed help across the entire arc that is, from setting goals to skill-building, to finding real projects, to networking, to tracking applications, to staying motivated.

Trying to solve all of them would have produced a broad but shallow product. So I looked for the point where three conditions overlapped:

High user frustration + weak existing solutions + a meaningful opportunity for AI

Understanding the user journey using JBTD

That led me to focus the first version on:

Finding a relevant product problem → turning it into a realistic design challenge → building proof of skill → connecting that skill to relevant companies.

Understanding Target market

Target User

Build with AI to move at founder speed

I chose Lovable to design in 2025 and build the complete app from scratch because it let me make product decisions at the speed of my research - Vibe coding, API integrations via Supabase, full responsive app. 15 days from first commit to working product.

Design evolution

CLICK CARDS TO READ 2025 Vs 2026 PROCESS

2026 - A more intentional rebuild

Rebuilt around a clearer core flow, a consistent design system, and stronger handling of empty results, unsupported files, and other edge cases.

Focused on the core value proposition

I simplified the experience further and only focussed on the core flow so that backend can be managed well. And this time I worked with newer tech such as Claude Code to have full control on my design & development without burning pockets.

Step 1: Choose a problem

Choosing a real user problem

Step 2: Generate the brief (AI transforms the problem into a structured challenge)

Getting a full brief for case study

Step 3: Match relevant Startups

Reaching out to relevant startups

Designed for the edge cases & different states

I made user flows in Figma to identify possible edge cases. I used GPT & Claude for quality check of the states and edge cases.

Edge cases & states

Created Design System

I built the design system manually but actively used Figma AI & Claude to fasten up the process without loosing the control. I also changed the brand color from Purple (AI generated) to Yellow to provide a friendly, positive and approachable vibe to the user.

Design System (Manual & Claude)

Prototyped in Claude

Launching soon

My plan is to launch it in November 2026 by deploying on Vercel.

Reflections

This project built my skills on building products

I thoroughly enjoyed finding a problem, calibrating solutions, understanding the product-market fit, competitive analysis, figuring out constraints, setting brand guidelines & design system, designing & using AI to make the process efficient while maintaining design quality.

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