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Hey HN, I’m the founder of SalaryScript, and I wanted to share a project I’ve been working on for over a year: a comprehensive negotiation playbook tailored specifically for big tech roles.

I’ve navigated the FAANG hiring gauntlet multiple times myself, with stints at FAANG companies, so I know firsthand how opaque and high-stakes these negotiations can be. I wrote SalaryScript based on my experience, insights from a dozen FAANG-alumni colleagues, and lessons from recruiters I’ve worked with over the years. We’ve pooled perspectives from engineers, PMs, and execs who’ve collectively negotiated millions in total compensation.

Think of it as a “golden rule” book for tech negotiations. It covers everything from decoding offer letters and leveraging competing offers to scripting responses for common recruiter tactics, handling equity cliffs, and navigating relocation packages. No fluff — just battle-tested scripts, templates, and strategies that have helped people increase their total comp by 30–50% on average.

One contributor, a former Meta engineering manager, shared how he turned a $300K offer into $550K by reframing the RSU vesting conversation. Another, an ex-Apple product lead, broke down the psychology of why “total comp” framing often beats focusing on base salary alone.

Since launching last year at an introductory price of $19, we’ve crossed 1,000+ downloads and sales. Demand has been strong, and as word has spread, we’ve gradually raised the price.

If you’re prepping for interviews or staring at an offer right now, this might be the edge you need.

If you’re interested, you can check it out at salaryscript.com.

Would love your thoughts, war stories, or questions like what’s the biggest negotiation win (or fail) you’ve had in tech?

Cheers

Comments URL: https://news.ycombinator.com/item?id=47083163

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The DOJ released ~3.5M pages of Epstein documents across 12 datasets. Buried in them are 207 academic papers and 14 books that nobody was really talking about. From what I understand these papers aren't usually freely accesible, but since they are public documents, now they are.

I don't know, thought it was interesting to see what this dude was reading. You can check it out at jeescholar.com

Pipeline: 1. Downloaded all 12 DOJ datasets + House Oversight Committee release 2. Heuristic pre-filter (abstract detection, DOI regex, citation block patterns, affiliation strings) to cut noise 3. LLM classifier to confirm and extract metadata 4. CrossRef and Semantic Scholar APIs for DOI matching, citation counts, abstracts 5. 87 of 207 papers got DOI matches; the rest are identified but not in major indexes Stack: FastAPI + SQLite (FTS5 for full-text search) + Cloudflare R2 for PDFs + nginx/Docker on Hetzner. The fields represented are genuinely iteresting: there's a cluster of child abuse/grooming research, but also quantum gravity, AGI safety, econophysics, and regenerative medicine. Each paper links back to its original government PDF and Bates number. For sure not an exhaustive list. Would be happy to add more if anyone finds them.

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hey, have we (collectively) examined Apollonius circles vs the three-body problem? like via motivic geometry over dynamic parameterization?

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Comments URL: https://news.ycombinator.com/item?id=47082872

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Comments URL: https://news.ycombinator.com/item?id=47082870

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Comments URL: https://news.ycombinator.com/item?id=47082799

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Comments URL: https://news.ycombinator.com/item?id=47082795

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Comments URL: https://news.ycombinator.com/item?id=47082762

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