FormSlayer is a privacy-first browser extension designed around a deceptively complex product problem: job seekers repeatedly enter the same identity, contact, work history, and eligibility information across fragmented hiring portals, but every portal structures that information differently. I designed the product as a human-centered automation layer, not a blind autofill tool. It accelerates the repetitive work, identifies what still requires human judgment, and keeps sensitive data local so speed never comes at the cost of trust, accuracy, or user control.
Applying for roles is not one workflow. It is the same information model repeatedly forced through dozens of inconsistent interfaces. Each hiring portal phrases questions differently, splits fields in different places, chains location inputs in its own order, and buries required uploads or eligibility questions in different parts of the page.
The product challenge was not simply reducing typing. It was designing automation that understood its own limits. Travel willingness, authorization status, demographic choices, role-specific prompts, and document uploads often require context or consent. FormSlayer needed to accelerate the repetitive work while making the remaining decisions more visible, not less.
The strategic decision was to separate stored identity from moment-of-application judgment. The profile workspace organizes stable information into familiar domains: contact, location, professional background, application preferences, and optional demographic details. That gives the system enough structure to act quickly without asking users to rebuild their history for every site.
On the application page, one controlled fill action maps saved answers onto the form in front of the user. Labels vary across portals, but the underlying intent is often the same; the extension interprets meaning rather than relying on exact wording. For fields that can be inferred safely, such as city and state from postal code or common eligibility formats, the product reduces friction without asking the user to micromanage every input.
The key UX principle is transparency. Open-ended prompts, role-specific questions, uploads, and sensitive choices remain visible because they still belong to the applicant. A live count of required fields left, plus optional markers on gaps, keeps the tool in an assistive role: fast where confidence is high, explicit where human review is still required.
Job applications contain identity data, employment history, eligibility information, and optional demographic fields. FormSlayer keeps saved settings on the user's device and does not send profile data to remote servers. That architecture is a product decision as much as a technical one: the value of automation disappears if users cannot trust where their information goes.
Optional categories stay optional by design. Users can store only what they are comfortable reusing, and the extension applies only the information they have chosen to provide. The project is open source under MIT so the behavior can be inspected directly, reinforcing the product's position as a transparent assistant rather than a black-box automation layer.