Parallax
Parallax
Reimagining job search as a conversational AI career copilot
Reimagining job search as a conversational AI career copilot
I designed and built Parallax to solve a personal pain point: the high friction, manual nature of modern job search. Parallax is an AI-first mobile web app that surfaces hidden startup opportunities in real-time through a conversational interface. By shifting the experience from manual browsing to AI-powered automation, I'm building toward a career copilot that autonomously manages the search end-to-end.
I designed and built Parallax to solve a personal pain point: the high friction, manual nature of modern job search. Parallax is an AI-first mobile web app that surfaces hidden startup opportunities in real-time through a conversational interface. By shifting the experience from manual browsing to AI-powered automation, I'm building toward a career copilot that autonomously manages the search end-to-end.
I designed and built Parallax to solve a personal pain point: the high friction, manual nature of modern job search. Parallax is an AI-first mobile web app that surfaces hidden startup opportunities in real-time through a conversational interface. By shifting the experience from manual browsing to AI-powered automation, I'm building toward a career copilot that autonomously manages the search end-to-end.
Role
Role
Founder & Designer
Founder & Designer
Scope
Scope
Product Strategy AI Conversation Design Interaction & Visual Design User Research AI-assisted Development
Product Strategy AI Conversation Design Interaction & Visual Design User Research AI-assisted Development
Collaborators
Collaborators
Technical Co-founder (Engineering & Product Strategy Collaboration)
Technical Co-founder (Engineering & Product Strategy Collaboration)
Timeline
Timeline
Oct 2025 - Present (Closed beta launched in Dec 2025)
Oct 2025 - Present (Closed beta launched in Dec 2025)
THE PROBLEM
THE PROBLEM
When I entered the job market recently, I was struck by how broken the search experience felt despite the "AI revolution". I found myself trapped in a 100-hour-a-month cycle of manual work that lacked both efficiency and intelligence. Three systemic gaps emerged —
When I entered the job market recently, I was struck by how broken the search experience felt despite the "AI revolution". I found myself trapped in a 100-hour-a-month cycle of manual work that lacked both efficiency and intelligence. Three systemic gaps emerged —
When I entered the job market recently, I was struck by how broken the search experience felt despite the "AI revolution". I found myself trapped in a 100-hour-a-month cycle of manual work that lacked both efficiency and intelligence. Three systemic gaps emerged —
Fractional Discovery
Fractional Discovery
Fractional Discovery
Fractional Discovery
Fractional Discovery
High-growth startup roles stay buried in fragmented ATS systems (Ashby, Greenhouse, Lever) and don't reach LinkedIn until flooded with applicants.
High-growth startup roles stay buried in fragmented ATS systems (Ashby, Greenhouse, Lever) and don't reach LinkedIn until flooded with applicants.
High-growth startup roles stay buried in fragmented ATS systems (Ashby, Greenhouse, Lever) and don't reach LinkedIn until flooded with applicants.
High-growth startup roles stay buried in fragmented ATS systems (Ashby, Greenhouse, Lever) and don't reach LinkedIn until flooded with applicants.
High-growth startup roles stay buried in fragmented ATS systems (Ashby, Greenhouse, Lever) and don't reach LinkedIn until flooded with applicants.
Missing Context
Missing Context
Missing Context
Missing Context
Missing Context
Job listings lack critical data like funding rounds, immigration support, and growth stage, essential for making decisions, but requiring hours of cross-referencing.
Job listings lack critical data like funding rounds, immigration support, and growth stage, essential for making decisions, but requiring hours of cross-referencing.
Job listings lack critical data like funding rounds, immigration support, and growth stage, essential for making decisions, but requiring hours of cross-referencing.
Job listings lack critical data like funding rounds, immigration support, and growth stage, essential for making decisions, but requiring hours of cross-referencing.
Job listings lack critical data like funding rounds, immigration support, and growth stage, essential for making decisions, but requiring hours of cross-referencing.
Manual Overhead
Manual Overhead
Manual Overhead
Manual Overhead
Manual Overhead
I was spending 100+ hours monthly tracking spreadsheets and applications rather than preparing for interviews. The administrative work eclipsed the actual career strategy.
I was spending 100+ hours monthly tracking spreadsheets and applications rather than preparing for interviews. The administrative work eclipsed the actual career strategy.
I was spending 100+ hours monthly tracking spreadsheets and applications rather than preparing for interviews. The administrative work eclipsed the actual career strategy.
I was spending 100+ hours monthly tracking spreadsheets and applications rather than preparing for interviews. The administrative work eclipsed the actual career strategy.
I was spending 100+ hours monthly tracking spreadsheets and applications rather than preparing for interviews. The administrative work eclipsed the actual career strategy.
APPROACH
APPROACH
Strategy: Finding the Competitive Edge
Strategy: Finding the Competitive Edge
Strategy: Finding the Competitive Edge
Strategy: Finding the Competitive Edge
Strategy: Finding the Competitive Edge
My strategy was to move away from the "Aggregator" model (LinkedIn/Indeed) and focus on a "Direct-to-Source" model for high-growth startups. I prioritized real-time integrations with startup ATS systems (Greenhouse, Lever) to surface roles before they hit mainstream boards, leveraged GenAI to enrich listings with market data like funding rounds and headcount growth, and pivoted the value proposition from a tool you "use" to an agent you "direct", enabling automation over repetitive searching.
My strategy was to move away from the "Aggregator" model (LinkedIn/Indeed) and focus on a "Direct-to-Source" model for high-growth startups. I prioritized real-time integrations with startup ATS systems (Greenhouse, Lever) to surface roles before they hit mainstream boards, leveraged GenAI to enrich listings with market data like funding rounds and headcount growth, and pivoted the value proposition from a tool you "use" to an agent you "direct", enabling automation over repetitive searching.
My strategy was to move away from the "Aggregator" model (LinkedIn/Indeed) and focus on a "Direct-to-Source" model for high-growth startups. I prioritized real-time integrations with startup ATS systems (Greenhouse, Lever) to surface roles before they hit mainstream boards, leveraged GenAI to enrich listings with market data like funding rounds and headcount growth, and pivoted the value proposition from a tool you "use" to an agent you "direct", enabling automation over repetitive searching.
Design Approach: Creating a Conversational Interface
Design Approach: Creating a Conversational Interface
Design Approach: Creating a Conversational Interface
Design Approach: Creating a Conversational Interface
Design Approach: Creating a Conversational Interface
The design challenge was making a conversational interface feel as efficient as a professional dashboard for high-stakes career decisions. I chose conversational AI because dialogue naturally captures what users want and how they refine their thinking, generating behavioral data needed to build truly autonomous assistance. The approach focused on progressive trust-building, lowering barriers for new users while revealing patterns that inform future AI capabilities.
The design challenge was making a conversational interface feel as efficient as a professional dashboard for high-stakes career decisions. I chose conversational AI because dialogue naturally captures what users want and how they refine their thinking, generating behavioral data needed to build truly autonomous assistance. The approach focused on progressive trust-building, lowering barriers for new users while revealing patterns that inform future AI capabilities.
The design challenge was making a conversational interface feel as efficient as a professional dashboard for high-stakes career decisions. I chose conversational AI because dialogue naturally captures what users want and how they refine their thinking, generating behavioral data needed to build truly autonomous assistance. The approach focused on progressive trust-building, lowering barriers for new users while revealing patterns that inform future AI capabilities.
Active Job Discovery
Active Job Discovery
Active Job Discovery
Active Job Discovery
Active Job Discovery
Chat-based search with suggested prompts and natural language queries. Users refine through dialogue, browse results as scrollable cards or drawer view, and bookmark jobs for quick access.
Chat-based search with suggested prompts and natural language queries. Users refine through dialogue, browse results as scrollable cards or drawer view, and bookmark jobs for quick access.
Chat-based search with suggested prompts and natural language queries. Users refine through dialogue, browse results as scrollable cards or drawer view, and bookmark jobs for quick access.
Chat-based search with suggested prompts and natural language queries. Users refine through dialogue, browse results as scrollable cards or drawer view, and bookmark jobs for quick access.
Chat-based search with suggested prompts and natural language queries. Users refine through dialogue, browse results as scrollable cards or drawer view, and bookmark jobs for quick access.
Proactive Notifications
Proactive Notifications
Proactive Notifications
Proactive Notifications
Proactive Notifications
Users define alert criteria to receive curated opportunities bi-weekly. Emails surface roles within 48 hours of posting with direct application access, eliminating the need to actively check the app.
Users define alert criteria to receive curated opportunities bi-weekly. Emails surface roles within 48 hours of posting with direct application access, eliminating the need to actively check the app.
Users define alert criteria to receive curated opportunities bi-weekly. Emails surface roles within 48 hours of posting with direct application access, eliminating the need to actively check the app.
Users define alert criteria to receive curated opportunities bi-weekly. Emails surface roles within 48 hours of posting with direct application access, eliminating the need to actively check the app.
Users define alert criteria to receive curated opportunities bi-weekly. Emails surface roles within 48 hours of posting with direct application access, eliminating the need to actively check the app.
SOLUTION
SOLUTION
By leveraging AI-assisted development (Figma, Lovable, Claude Code, Vercel), I moved from blank canvas to functional closed beta in 12 weeks. The mobile web app launched in December 2025 with 20+ active users, testing whether job seekers will adopt conversational AI and trust real-time hidden job sources for high-stakes career decisions, the first step toward agentic AI that autonomously manages job search.
By leveraging AI-assisted development (Figma, Lovable, Claude Code, Vercel), I moved from blank canvas to functional closed beta in 12 weeks. The mobile web app launched in December 2025 with 20+ active users, testing whether job seekers will adopt conversational AI and trust real-time hidden job sources for high-stakes career decisions, the first step toward agentic AI that autonomously manages job search.
By leveraging AI-assisted development (Figma, Lovable, Claude Code, Vercel), I moved from blank canvas to functional closed beta in 12 weeks. The mobile web app launched in December 2025 with 20+ active users, testing whether job seekers will adopt conversational AI and trust real-time hidden job sources for high-stakes career decisions, the first step toward agentic AI that autonomously manages job search.
