ReplylessAI

I used the Antler MENA cohort environment to sharpen the audience, workflow problem, product promise, and MVP scope before committing to interface directions.

I defined the information architecture, intent-based inbox model, interaction patterns, visual language, and reusable components as one coherent product system.

Using AI coding agents, I converted design intent into a functional React application, directing implementation through structured prompts, product specifications, acceptance criteria, and continuous visual QA.

I reviewed generated implementation against the intended user flows, corrected interaction and hierarchy gaps, refined the experience across breakpoints, and deployed the product and marketing surfaces.

Instead of forcing users into a traditional unread/starred/archive workflow, I designed the inbox around real-world mental buckets: Important, Job Applications, Payments, Newsletters, Updates, and Other. This gives structure immediately and reduces the "where do I even start?" problem.

Quick actions like remind, complete, and delete live where the user is already looking. The goal was to remove toolbar hunting and make triage feel lightweight enough to do continuously instead of in long cleanup sessions.

The AI assistant was designed as an on-demand layer over the inbox, not a takeover. Users can search messages, find tasks, draft replies, and summarise threads inside a familiar chat surface while still keeping the original email context visible.

The visual direction uses soft gradients, light surfaces, and simple iconography to make a productivity tool feel approachable. The website and product were designed to tell the same story: this is serious software, but it should still feel easy to start using.