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A structured reflective essay analysing a real workplace ethical dilemma through a step-by-step decision-making framework.
The piece walked through the process of recognising an ethical conflict, gathering relevant facts, identifying available options, testing each option against legal and moral standards, and arriving at a reasoned decision — all grounded in a genuine personal experience.
The writing balanced personal reflection with analytical rigour, demonstrating the ability to present complex reasoning in a clear, readable structure.
Delivered as a fully formatted academic essay suitable for professional or institutional submission.
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Try Verity is an AI-powered interview coaching platform that creates realistic interview simulations based on a candidate's actual resume and target job description.
For this challenge, I used Google Stitch as the center of a real product redesign workflow.
Instead of building a mockup from scratch, I imported screenshots from the existing product, generated redesigned interfaces, and used Stitch to transform those concepts into production-ready UI code.
My workflow:
• Existing Try Verity screens → AI redesign mockups
• Mockups imported into Google Stitch
• Stitch-generated UI and front-end structure
• Implementation and integration using Codex
• Integration into the real application
The goal was not to create a prototype, but to modernize an existing product while preserving functionality, workflows, and business logic.
The redesign covered the landing page, interview workspace, recruiter feedback experience, reporting dashboard, pricing pages, and onboarding flow.
Key improvements:
• Complete landing page redesign
• Interview workspace redesign
• Recruiter-style feedback experience
• Modern SaaS visual language
• Improved information hierarchy
• Better usability and readability
• Enterprise-grade UI patterns
Tools used:
• Google Stitch
• ChatGPT
• Codex
• Next.js
• React
• TypeScript
• Tailwind CSS
Application Web: https://www.tryverity.co/
Video Walkthrough:https://youtu.be/iITu8t9-5pw
Google Stitch became the bridge between visual exploration and implementation, allowing me to iterate much faster than a traditional design-to-development workflow.
Thanks to the Google Stitch team for building tools that make interface iteration dramatically faster.
Looks cool
We just wrapped a product design project for StitchedHealth, a clinical education platform built to improve how healthcare professionals make real-world decisions.
The product had strong content from day one.
Expert-led clinical discussions, real-world case scenarios, peer reasoning comparisons, evidence alignment. The foundation was already there.
What it needed was an interface that could carry all of that without overwhelming the people using it.
Clinicians are time-constrained. They don't have patience for friction. And the content they're working through (complex, layered, high-stakes) can easily become a cognitive wall if the design isn't doing its job.
We took a lot of design inspiration from conversational AI products like Perplexity. Content streams in as users move through each scenario, and they can interact with it through open prompts or structured questions. The whole experience feels modern without losing the clarity that a clinical audience needs.
So we focused on a few things:
Clearer decision moments to guide engagement
Simpler peer insight surfacing to reduce cognitive load
Smoother transitions between steps to keep momentum
The result is a platform that feels approachable without being dumbed down. A clean progression from expert-led video through interactive case work, peer comparison, and evidence alignment.
If you're working on a product in a complex space and the experience isn't keeping up with the content, that's usually a design problem, not a content one.
Book a call and let's talk about it: cal.com/jacob-lovett
9
This is so clean
Selected is an AI-powered Job Search Copilot that transforms application emails into actionable career guidance.
Job seekers often manage applications across Gmail, Outlook, LinkedIn, and company career pages, making it difficult to track recruiter responses, interview schedules, and follow-ups. Selected automatically discovers application activity from connected inboxes and organizes it into a centralized, intelligent workspace.
Instead of simply tracking applications, Selected helps users understand what to do next. Through AI-powered recommendations, strategic summaries, follow-up suggestions, and job search insights, the product turns a chaotic inbox into a proactive job search strategy.
Link to prototype
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