HiredVoices
AI-curated interview stories, salary benchmarks, and DSA trends for job seekers.
Tagline
What Google asks right now
The interview intelligence layer for engineers
A sharper way to prep than Glassdoor
Stop guessing. Study what shows up now
The interview intelligence layer for software engineers.
The product is not a generic job board; it combines interview experiences, salary data, and question-frequency analysis into a single decision-support layer for candidates.
A sharper alternative to Glassdoor and Blind for interview prep.
Glassdoor has salaries and reviews, Blind has anonymous chatter, but HiredVoices explicitly organizes recent interview rounds, compensation examples, and trending questions into prep-ready content.
Stop preparing blindly: focus on the questions and companies that are showing up right now.
The page emphasizes last-3-month question frequency and recent company-specific stories, which is a strong pain-killer message for candidates who are over-prepping low-value material.
Primary user
Software engineer candidate preparing for interviews at FAANG and high-paying product companies
ICP #1
Mid-level software engineer at a mid-size product company interviewing for L4/L5 roles at Google, Stripe, or Microsoft
Pain
They waste hours on generic prep because they don't know which questions are actually repeating, what rounds each company is running, or how compensation is trending by role.
Why this solves
HiredVoices shows real interview experiences, recurring DSA questions, and compensation benchmarks in one place, so they can focus prep on what is demonstrably showing up in interviews.
ICP #2
Fresher software engineer in India targeting AMTS/SDE-1 roles at Salesforce, Oracle, or Google
Pain
They have no reliable sense of salary bands, interview format, or how to prepare beyond random YouTube advice and LeetCode grind.
Why this solves
The site surfaces fresher offers like Salesforce AMTS, interview round breakdowns, and the exact questions recurring in recent reports, which is more actionable than generic prep content.
ICP #3
Senior software engineer comparing offers and negotiating compensation after final rounds
Pain
They struggle to anchor negotiation because salary data is fragmented, anecdotal, and often stale by the time they see it.
Why this solves
HiredVoices provides recent compensation posts with fixed pay figures and company/role context, making it easier to benchmark and push back on low offers.
Strengths
- +Clear value proposition at the top: interview insights plus salary benchmarks, not just generic career advice.
- +Strong proof of specificity with real company examples like Google L4, Stripe SDE-1, Oracle SWE5, and Microsoft vs eBay.
- +The trending questions section is a smart differentiator because it turns raw anecdotes into prep priorities.
Weaknesses
- −The homepage repeats itself a lot and feels like a feed, not a product story; there is almost no explanation of how the AI refinement works.
- −There is no visible trust mechanism: no data source details, no methodology, no sample size, no freshness guarantees beyond a few dates.
- −The audience is too broad on the surface; it says career guidance, but the content is overwhelmingly software-engineer interview prep.
- −The call to action is weak; 'Search' is not a compelling conversion path for first-time visitors.
- −The product's unique edge versus Glassdoor/Blind/Levels.fyi is implied, not stated bluntly.
Fix these
- Rewrite the hero around a narrow promise: recent interview patterns and compensation signals for software engineers at top companies.
- Add a methodology block explaining where data comes from, how AI summarizes it, and how question frequency is calculated.
- Create separate landing paths for interview prep, salary research, and company research instead of one blended homepage.
- Introduce stronger CTAs like 'See what Google L4 candidates were asked this month' or 'Check your offer against recent comp reports.'
- Add credibility signals: number of reports indexed, freshness stats, and company coverage counts.
Drop-in replacement copy
Headline
Recent interview signals for engineers
See what top tech companies are asking, paying, and repeating right now.
Focus on what’s actually repeating
See trending interview questions by company, role, and recency, so you stop overpreparing for low-signal topics. Each question links to the underlying LeetCode problem and original report.
Compare comp with real context
Browse recent salary and compensation benchmarks with company and role detail, not stale screenshots. Use it to sanity-check offers and negotiate with a better anchor.
Read cleaner interview stories
HiredVoices uses AI to turn messy reports into concise summaries with round-by-round structure. You get the part that matters fast, without the noise.
Research companies before you interview
Explore pages for Google, Stripe, Meta, Amazon, Microsoft, Oracle, Uber, and Salesforce. Find recent stories, technical blog deep dives, and the patterns candidates keep seeing.
FAQ
Where does the data come from?
It aggregates interview experiences, compensation posts, and technical content from across the internet, then organizes it by company, role, date, and topic. The AI layer summarizes and tags the content; it does not invent the source material.
How fresh is the information?
The product prioritizes recent reports and highlights trends from the last 3 months where possible. Freshness is shown in the UI so you can judge whether a signal is current or stale.
Is this only for software engineers?
Right now, yes. It’s built specifically for engineers interviewing at top tech and high-paying product companies, where question patterns and comp signals matter most.
How is this different from Glassdoor or Blind?
Glassdoor is broad and Blind is noisy. HiredVoices is organized around interview prep: recent rounds, repeated questions, compensation context, and company-specific signal you can use immediately.
Can I use it for salary negotiation?
Yes. That’s one of the main use cases. Recent comp examples with role and company context make it easier to benchmark your offer and decide whether to push back.
I built HiredVoices because interview prep is weirdly broken. You can grind LeetCode for weeks and still miss the actual questions, rounds, and salary signals companies are using right now. This pulls recent interview stories, comp data, and trending DSA patterns into one place.
Most candidates study the wrong things. They read random blogs, watch generic prep videos, and hope the interview looks like last year. HiredVoices shows recent company-specific interview stories, salary benchmarks, and the questions repeating this month.
I spent way too long turning messy interview reports into something useful. The hard part wasn’t collecting data. It was making it readable: company, role, date, round, salary, question frequency, and AI summaries that remove the noise. That’s the product.
Salary data gets stale fast. A number from 18 months ago is basically trivia. So I built HiredVoices around recent compensation posts with role context, fixed pay, and company tags, so engineers can anchor negotiations on what’s happening now.
You do not need to grind 500 random LeetCode problems. You need to know which questions are actually repeating for Google, Stripe, Microsoft, Meta, and the rest. HiredVoices surfaces the DSA patterns showing up in the last 3 months.
Negotiating without fresh comp data is just guesswork. By the time you find a salary post, the market has moved. HiredVoices keeps recent compensation examples in one place so you can sanity-check offers before you say yes.
Instead of 12 tabs, you get one search bar. Type a company and see interview stories, salary benchmarks, trending questions, and linked LeetCode problems. It’s basically the prep layer candidates kept building in spreadsheets.
Here’s the actual value: company pages. Open Google, Stripe, Oracle, Amazon, Microsoft, Meta, Uber, or Salesforce and instantly see recent interview experiences, comp reports, and technical patterns. Less browsing. More signal.
Candidates don’t need more motivation. They need fewer bad inputs. That’s why recent stories, tagged rounds, question frequency, and company-specific blog deep dives matter. The market changes too fast for generic advice.
If you’re interviewing at top tech companies, you already know the pain: Glassdoor is fragmented. Blind is noisy. LeetCode doesn’t tell you what’s actually being asked. HiredVoices pulls the useful stuff into one workflow.
Angle: narrow positioning around interview intelligence
I kept seeing the same problem with software engineers preparing for interviews: They had too much content and not enough signal. LeetCode tells you what could be asked. Glassdoor tells you old anecdotes. Blind tells you what people felt. None of them answer the real question: What are companies actually asking right now, and what compensation is still realistic? So I built HiredVoices. It pulls recent interview experiences, salary benchmarks, and repeated DSA questions into one place, then uses AI to turn messy reports into something usable. The goal is simple: help engineers spend less time guessing and more time preparing for the rounds, questions, and companies that are showing up today. If you're interviewing at Google, Stripe, Microsoft, Meta, or other high-paying product companies, I’d love feedback on the company pages and search flow.
Angle: compensation research and negotiation
One of the most frustrating parts of a job search is compensation research. By the time you find a salary post, it’s often stale, missing context, or buried in a thread you can’t trust. That’s especially painful when you’re comparing offers or trying to negotiate after final rounds. HiredVoices is my attempt to make comp research less chaotic for software engineers. It surfaces recent fixed pay and total comp context, tied to company and role, so you can get a clearer picture of what’s happening now. It also connects comp data to interview stories and company-specific prep so the page isn’t just a number. It’s a decision-making tool. If you’re currently comparing offers from companies like Microsoft, Salesforce, Google, or Stripe, I’d genuinely like to know whether the format makes this easier or still feels too fragmented.
Angle: build story and product methodology
I’ve been building HiredVoices around a simple idea: Candidates do better when the prep is tied to real patterns, not generic advice. That means showing: - recent interview stories - role and company context - repeated questions over the last 3 months - salary benchmarks with actual date freshness - links back to original sources The hardest part wasn’t collecting data. It was turning raw internet noise into something that feels trustworthy and actionable. So the product now focuses on recentness, company specificity, and clarity. No broad “career advice.” No endless feed. Just the signal that helps engineers decide what to study next. If you’ve ever prepared for a FAANG-style loop, I’d love your feedback on what would make this genuinely useful instead of just another content site.
No visuals for this kit yet.
Tagline
Recent interview signals for software engineers
Description
See recent interview stories, salary benchmarks, and repeating DSA questions for top tech companies in one place.
Maker's first comment
I built HiredVoices because I kept watching software engineers prepare the hard way: too many tabs, too much stale advice, and not enough signal about what companies are actually asking right now. A lot of the existing tools are useful in pieces, but the prep workflow is still scattered across Glassdoor, Blind, LeetCode, random blog posts, and spreadsheet notes. This started as a way to answer one question better: “What should I focus on for this company and role this month?” From there it became interview stories, comp benchmarks, question frequency, and company-specific technical deep dives in one place. The AI part is there to clean up the mess, not to replace the source data. I’d love feedback on the company pages, trust signals, and whether the search flow makes it easier to go from curiosity to action in under a minute.
Pinned maker comment
I’m most interested in whether the homepage makes the value obvious in the first 10 seconds, and whether the company pages feel more useful than Glassdoor/Blind for interview prep.
Meta
Preparing for Google feels random
Hypothesis: software engineers interviewing at Google, Stripe, Microsoft, and Meta want recent, company-specific prep more than generic advice. HiredVoices shows recent interview stories, recurring DSA questions, and salary benchmarks in one place.
Google Search
Google L4 interview questions this month
Hypothesis: candidates searching for company-specific interview prep are frustrated by stale results. HiredVoices surfaces recent interview experiences, question frequency, and comp context for top tech companies.
Reddit Promoted
Stop grinding random LeetCode problems
Hypothesis: r/leetcode and r/cscareerquestions readers want fewer generic prep tips and more evidence-based signals. HiredVoices highlights the questions and salary reports showing up recently for specific companies and roles.
Subreddits
r/leetcode
Share a data-backed breakdown of the top 20 most repeated DSA questions from the last 3 months across Google/Stripe/Meta reports
Rules: No obvious self-promo; lead with useful analysis and ask for critique on methodology
r/cscareerquestions
Post a practical guide on how to compare interview prep sources and spot stale salary data
Rules: Must be genuinely helpful; avoid link-dropping in the title; expect strict moderation on promo
r/techjobs
Share a salary benchmark roundup for engineers comparing offers at top product companies
Rules: Keep it specific and data-focused; no spammy launch language
r/cscareerquestionsEU
Ask for feedback on whether company-specific interview signals would help engineers outside the US too
Rules: Be transparent that the current data is US-heavy; invite discussion rather than pushing a product
r/ExperiencedDevs
Discuss how senior engineers actually research comp and interview patterns before switching jobs
Rules: High bar for quality; no beginner fluff; frame it as a research tool and ask for feedback
Communities
Publish build logs and a teardown of how you turned messy interview reports into a searchable product. Focus on the data pipeline, not the launch hype.
Share the customer research angle: what software engineers actually need when deciding where to interview and negotiate.
Engage in career and founder channels by asking for feedback on product positioning and trust signals for data-heavy tools.
Cold outreach template
{firstName}, I saw you were preparing for {context} and wanted to share something useful. I built HiredVoices to show recent interview stories, comp benchmarks, and the questions repeating for that company right now. If you want, I can send you the exact page for your role.
Product Hunt timing
Launch on Tuesday at 12:01 AM Pacific Time. PH traffic is strongest early Tuesday morning, and this ICP skews US-based software engineers who check tools before work; Tuesday avoids the weekend dead zone and gives you a full weekday cycle for comments, shares, and follow-ups.
Indie Hackers post ideas
- 01How I turned messy interview reports into a searchable product
- 02What I learned building an AI layer on top of public salary data
- 03The landing page changes that made interview prep feel specific, not generic
Competitor alternatives
Current tone of voice
Helpful, aspirational, and slightly polished/tech-career oriented; for example, it says "Unlock AI-Powered Real Interview Insights and Salary Benchmarks" and "Engineering Wisdom You Won't Find in Textbooks."
Your kit is ready. Sign up free to unlock, takes 10 seconds.
7 more X posts · 2 LinkedIn · Product Hunt copy · ad hooks · 100-user playbook · landing critique