How I Architected an AI-Orchestrated Workflow to End "Portal Fatigue

Like many of you, I hit a wall with the modern job-hunting tech stack. Between the fragmented dashboards, the endless "resume tailoring" services that feel like black boxes, and the subscription fatigue of paying monthly just to apply for jobs, I decided to build my own solution. I’m an AI engineer, so I stopped fighting the system and started building an orchestration layer to handle it for me. I’ve spent the last few months working on Highwires, an all-in-one dashboard designed to consolidate tracking, AI-powered resume tailoring, and interview prep. The Technical Challenge: Decoupling the Workflow The biggest hurdle wasn't the AI it was the data-entry bottleneck. Dealing with the "portal graveyard" (where one-click apps just redirect you to a broken registration page) is a massive time sink. I wanted to solve this by building a decoupled architecture where the AI orchestration layer handles the heavy lifting of tailoring without needing a manual interface for every single site. I’ve been iterating on: Automation Architecture: Reducing the latency between the AI tailoring engine and the application submission. Cost Structure: I’m experimenting with moving away from the standard SaaS subscription model to a one-time lifetime payment of $9.99 to cover server costs without recurring fees for the end user. What I’m Looking For I’m at the stage where I really need "brutal" feedback from the engineering community. Does this approach to decoupling the AI-orchestration from the UI actually feel like a time-saver to you? How do you all handle the server costs for utility-heavy apps without relying on monthly subscriptions? I’m not looking to spam; I’m genuinely interested to know if this solves a pain point you’ve felt or if I’m just building for my own niche workflow. Would love to hear your thoughts on the architecture and the pricing model!