Zuhayeer Musa and Zaheer Mohiuddin were software engineers at major tech companies in 2017 when they noticed a persistent problem: tech compensation was absurdly opaque. When engineers moved between companies, they had no reliable way to understand how their level at one company translated to another. Was a Google L5 equivalent to a Facebook E5 or a Microsoft 63? Glassdoor existed, but its salary data was self-reported, unverified, and increasingly outdated. The two founders realized that the entire tech industry lacked a trusted source of truth for compensation data — and they could build one as a side project.

The Simple HTML Table That Changed Tech Compensation

The first version of Levels.fyi was remarkably bare-bones: a simple HTML page with a table mapping engineering levels across Google, Facebook, Amazon, Apple, and Microsoft. No fancy design, no backend database, no user accounts. Just a clean reference table that answered the question engineers constantly asked each other: "What level would I be at your company?" Zuhayeer posted the site on Blind (the anonymous workplace discussion app popular among tech workers) and Hacker News. The response was immediate and overwhelming. Engineers had been craving this information for years, sharing it informally in private conversations and Slack channels. Levels.fyi simply made it public and organized. Within days, the site was getting thousands of visitors — all from organic sharing, with zero marketing spend.

Building the Data Flywheel

The level comparison table was the hook, but the real product was the compensation data that came next. Levels.fyi added a submission form where engineers could share their total compensation (base salary, stock grants, bonuses) along with their company, level, and years of experience. The data flywheel was elegant: engineers came for the level comparisons, stayed to see compensation data, and contributed their own data to help others. As more data came in, the site became more useful, which attracted more visitors, who submitted more data. Crucially, Levels.fyi implemented verification mechanisms — cross-referencing submissions against known compensation bands, flagging outliers, and requiring enough detail to make fabrication difficult. This data quality focus differentiated Levels.fyi from Glassdoor, where unverified submissions had eroded trust.

Community-Driven Growth Without Spending a Dollar

Levels.fyi's growth was entirely organic. Tech workers shared the site on Blind, Hacker News, Reddit (r/cscareerquestions), Twitter, and internal company Slack channels. Every compensation negotiation season drove a traffic spike as engineers looked up market rates before their performance review conversations. The site became the de facto reference for tech compensation discussions — when someone on Blind asked "Is this offer fair?", the answer was almost always "Check Levels.fyi." The founders never spent a dollar on advertising, SEO optimization, or growth marketing. The product was so genuinely useful that the community marketed it for free. Zuhayeer and Zaheer continued running Levels.fyi as a side project for the first two years, working on it nights and weekends while maintaining their full-time engineering jobs.

From Side Project to Platform

By 2020, Levels.fyi had become the definitive tech compensation platform, with millions of annual visitors and hundreds of thousands of verified compensation data points. The founders added premium features — salary negotiation coaching, career planning tools, and company-level compensation analytics — and transitioned to a freemium business model. The free tier (level comparisons and basic salary data) continued to drive massive traffic, while premium features converted a small percentage of users into paying customers. The founders eventually left their full-time jobs to focus on Levels.fyi, which was generating significant revenue from premium subscriptions and enterprise partnerships with recruiting firms. The platform had achieved something rare in tech: it became the trusted standard that replaced informal, unreliable information networks with structured, verified data.