interesting, this reframes the question to "how long would it take until something significant goes out of sync", in that case i do agree with you, there'll be some mysterious period of time the two universes staying in sync, potentially infinity
Fair point, I did try to include the job requirements in the before/after but couldn't integrate it in a pleasant way, but if you're interested here's the job post I used for the example: https://apply.workable.com/lucidya/j/47F7F41A30/
I think Resume.Ink is different because it generates a new PDF resume tailored specifically to the job you're applying to. While JSON Resume generates a cover letter. I think they actually complement each other quite well.
Yeah my bad, I just tried to delete my comment but too late.
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My useful feedback;
- I thought the UX was broken when there was no next button after answering questions
- It would be great if the homepage showed a real example (real JD, real before and after)
- There was a bug in my upload (Thomas Davis pdf if you are looking at the database). It hallucinated a whole job I've never had into my finished resume.
Don't worry, I'm pretty sure someone will find your comment useful
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Thanks for the feedback:
1. You're right, the UX can use some improvements there
2. I've just updated the landing page with a before/after example
3. Ooh, that's not good, thanks for reporting this, I'll look into it asap
I'm also working on a similar feature, it's simple but complicated too "merge" information in when using GPT's. I imagine you've encountered it too. If I say I have an array of interests ['music', 'gardening', 'racing'], and a GPT replies ['music', 'gardening', 'racing', 'competitive driving'], you don't want additive synonyms. And then more complicated is deletions, if it replies, ['gardening', 'racing', 'skydiving'], does that mean I want to remove 'music' or did it just forget to include it in the response so should I just merge the old and new array.
I'm probably going to open source a llm-structured-data-merge-thingy library (that has different merge strategies) in the near future.
an AI-native book reader that actually understands what you’re reading.
You highlight text, and the app infers intent and surfaces the right actions inline.
Examples:
Highlight a confusing paragraph → auto-suggests questions like “what does this term mean?” or “how does this relate to earlier chapters?”
Highlight a name → instant character context (no spoilers)
Highlight an argument → concise breakdown, assumptions, counterpoints
It works across EPUBs, PDFs, and papers, and the core rule is: AI should be assistive, never intrusive. No prompts required, no context switching.
Built it because I read a lot of dense material and hated breaking flow.