0 → 1

From zero to launch in under 12 weeks — building an enterprise vulnerability management platform now used by Fortune 500s and Ivy League universities.

Overview

I joined as the first and only product designer at a stealth-stage security startup focused on vulnerability management, a high-stakes and highly technical problem space. Over the course of a few months, I helped the team evolve from an early prototype to a production-ready product used by some of the world’s most security-conscious companies.

What made this experience unique wasn’t just the speed at which we had to move. It was how I used AI to compress timelines, expand creative exploration, and raise the quality bar. My process evolved to match the needs of fast-paced teams: nonlinear, modular, and deeply collaborative across product and engineering.

Role:
Founding Product Designer

Role:
Founding Product Designer

Focus:
End-to-end product design + brand + GTM assets

Focus:
End-to-end product design + brand + GTM assets

Timeline:
0 to live product in under 12 weeks

Timeline:
0 to live product in under 12 weeks

Deployed by:
Multiple Fortune 500s and Ivy League universities

Deployed by:
Multiple Fortune 500s and Ivy League universities

Process, Augmented

My design approach follows a core framework. Each step is deeply influenced by speed, quality, and leverage, especially through AI augmentation, which I’ve integrated into every phase. This allows me to explore more ideas, validate faster, and scale execution even as a solo designer.

These steps aren’t always linear. I move between them depending on product maturity and team needs.

Educate

Before jumping into Figma, I spend time deeply understanding the domain, users, and business context. This step sets the foundation for everything else.

My goal is to become just opinionated enough to contribute strategically from Day 1, while staying open to learning from users and stakeholders.

What I did

What I did

  • Reviewed pitch decks, early product docs, 1-pagers

  • Conducted async interviews with the founding team

  • Mapped out the competitive landscape

  • Researched common workflows in security tooling

  • Reviewed pitch decks, early product docs, 1-pagers

  • Conducted async interviews with the founding team

  • Mapped out the competitive landscape

  • Researched common workflows in security tooling

Generate

This is where research becomes actionable. I create a set of foundational artifacts that both align the team and feed custom GPTs for design acceleration.

Artifacts I created:

Artifacts I created:

  • Core personas and key user goals

  • End-to-end user journey mapping

  • High-level IA and navigation structures

  • Industry overview and terminology glossary

  • GPT-ready prompts for idea & design generation

  • Core personas and key user goals

  • End-to-end user journey mapping

  • High-level IA and navigation structures

  • Industry overview and terminology glossary

  • GPT-ready prompts for idea & design generation

By treating this step as both a discovery phase and a prompt-engineering step, I multiplied the number of good ideas I could explore downstream, without losing fidelity.

AI Augment

AI Augment

Created a dedicated GPT trained on internal docs + research artifacts → used for idea generation & edge case handling

Created a dedicated GPT trained on internal docs + research artifacts → used for idea generation & edge case handling

Design

Once the core ideas are aligned, I move into fast, iterative design sprints.

A blend of AI and craft:

A blend of AI and craft:

  • Used custom GPTs to generate ACS-style wireframes

  • Synthesized output into clean, strategic design direction

  • Built high-fidelity designs in Figma with modular components

  • Prioritized key workflows

  • Created a visual system that felt modern and enterprise-ready

  • Used custom GPTs to generate ACS-style wireframes

  • Synthesized output into clean, strategic design direction

  • Built high-fidelity designs in Figma with modular components

  • Prioritized key workflows

  • Created a visual system that felt modern and enterprise-ready

AI Augment

GPT suggested wireframe layouts, decision trees, and even error states — I still designed, but faster and with more inputs.

AI Augment

GPT suggested wireframe layouts, decision trees, and even error states — I still designed, but faster and with more inputs.

Validate

Not every screen needs perfect polish at this stage, but key workflows did. Based on feedback, I tightened the copy, clarified flows, and reduced cognitive load where needed.

I validated direction across 3 layers:

  1. AI-based heuristics & usability tools

  2. Internal stakeholder reviews with founders and engineers

  3. Customer feedback from design partners and early users

I validated direction across 3 layers:

  1. AI-based heuristics & usability tools

  2. Internal stakeholder reviews with founders and engineers

  3. Customer feedback from design partners and early users

Ship

This was a highly collaborative phase. Fast feedback cycles, shared language, and mutual respect made it work.

I worked closely with engineering to ensure smooth handoff and high-fidelity implementation:

I worked closely with engineering to ensure smooth handoff and high-fidelity implementation:

• Annotated all designs for handoff using Figma comments

  • Created interactive specs for complex components

  • Used ProBlock to sync design tokens + color variables

  • Built and shipped select components in V0.dev

  • Answered async questions and did quick Zoom reviews

  • Annotated all designs for handoff using Figma comments

  • Created interactive specs for complex components

  • Used ProBlock to sync design tokens + color variables

  • Built and shipped select components in V0.dev

  • Answered async questions and did quick Zoom reviews

Beyond the Product

Also supported the team by designing:

Also supported the team by designing:

  • Logo

  • Landing page

  • Marketing one-pagers

  • Pitch templates

  • Logo

  • Landing page

  • Marketing one-pagers

  • Pitch templates

Outcomes

Outcomes

  • Launched MVP used by Fortune 500s and Ivy Leagues

  • Accelerated product iteration speed by integrating AI

  • Created a scalable design foundation (flows, system, assets)

  • Shipped both product and brand assets in parallel

  • Launched MVP used by Fortune 500s and Ivy Leagues

  • Accelerated product iteration speed by integrating AI

  • Created a scalable design foundation (flows, system, assets)

  • Shipped both product and brand assets in parallel

Reflection

Despite being a solo designer, I helped the team go from concept to working product in under 12 weeks.

What worked well

What worked well

  1. AI accelerated exploration and allowed broader, deeper iteration

  2. Close team collaboration meant fewer silos and more momentum

  3. My ability to shift from product to brand/marketing work made me a force multiplier

What I'd improve next time

What I'd improve next time

  1. Invest in micro-interactions and empty states earlier

  2. Introduce customer onboarding sooner to tighten activation

  3. Plan a longer-term design system with token management from day 1

If you're building something ambitious and need a designer who moves fast without sacrificing quality — let’s talk.

If you're building something ambitious and need a designer who moves fast without sacrificing quality — let’s talk.

Let's Talk

Let's Talk

Let's Talk

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