As developers, we attempted an AI resume parser and a masonry layout engine, and we need brutal, objective feedback about the edge cases.

[u/OrganicReindeer3467]

Hello everyone,

My developer friend and I decided to build a resume builder (JobFix.ai) that would address a problem we continuously faced, which is the painful amount of time it takes to customize every resume to a specific job description.

Full disclosure-we are both developers, not designers. This explains why the UI was built using an AI, and why we've been working on improving the post-login screen over the last few days, switching to a softer cream (#FFF5E2) to make it feel a bit more upscale, rather than being too stark. Do you think it actually feels clean, or do you find it to be obvious that a couple of developers built it?

Here's a summary of what we've managed to create thus far:

* Unstructured PDF Parsing: The system can process complex PDFs, with all text mapped and categorized in a structured database.

* Skill Gap Analysis: Input a job description, and the engine scans your parsed resume and pinpoints the crucial missing skills needed for that position.

* Auto-categorization: it automatically recognizes and categorizes skills appropriately (like separating Languages from Frameworks).

* Dynamic Masonry layouts: This was the most complex feature we implemented-auto-adapting layouts that automatically flow content and eliminate any unsightly whitespace, ensuring that everything fits on one page perfectly.

Now for the tricky part, we need the eyes of users:

We're currently trying to put the parser to the test, and we need everyone who is willing to upload their resumes and try to make it fail!

Are there any PDF formats it totally fails to extract from?

Do the masonry templates appear strangely on your screen dimensions?

Is this a tool that you would actually find useful enough to (potentially) pay a small, coffee-cup sized amount for, once it's all ironed out?

We do have an ATS Score Checker and a "1-Click Tailor" button planned, but the core of the tool needs to be perfect before moving forward.

If you can spare a couple of minutes, we would greatly appreciate you taking it for a test drive and a good roasting-let me know in the comments and I will personally send you a link, so as not to spam everyone.

We truly value your time and brutally honest critique.

[u/mmt2111]

Roast from the landing-page side: your riskiest edge case is not masonry, it is trust. You are asking people to upload one of the most personal PDFs they own, but the first screen does not immediately tell me what happens to that file.

I would add a small privacy/trust strip before or beside "Start building free":

• whether resumes are stored or deleted
• whether the AI trains on uploads
• whether users can use the ATS checker without creating an account
• what file types/sizes you support

The other issue is proof. "Candidates hired at" is visually strong, but it reads like borrowed credibility unless you explain what it means. If those are just companies users later joined, say that. If they are logos of actual users/customers, add a tiny qualifier.

For parser testing, I would also publish 5 weird resume examples you want people to break: two-column PDF, tables, icon-heavy Canva resume, academic CV, and non-English resume. That gives testers a target instead of a vague "try to make it fail" ask.

[u/OrganicReindeer3467 → u/mmt2111]

Asking for someone's resume is a big deal, so we'll include a very prominent privacy strip next to the CTA detailing how we store data, what data we use for AI training, and what file types we support. Great point about the 'Candidates hired at', we'll clarify that immediately so it's not perceived as inflated credibility.

I love that idea about 5 very concrete examples of 'weird' resume templates that people have to break (2-column, Canva, academic, etc). That makes the request for a resume that much more specific. Really appreciate the write-up.