Product career lessons from Binance, N26, Google, and beyond

Executive overview

Most product strategy debates are wasted effort. If you can test a hypothesis in days, you don't need a strategy — you need faster experiments. The fastest path from hypothesis to data is your strategy.

Mayur Kamat has led product at Google, Binance, Agoda, and N26. Across those roles, a few principles recur: join fast-growing companies to compound learning, play to your strengths rather than fixing weaknesses, and stay in the details on whatever problem has the highest leverage for the business right now.

Build experimentation into your product culture — it's the only way to make product management a science, not a matter of who shouts loudest.

Operating at Binance's extreme pace

• Binance went from zero to ~$400B valuation in five years with 2,000 employees — a scale no prior tech company matched at that speed
• Flat structure: CZ had ~55 direct reports; most employees were just one level from the CEO
• Leadership met every day at 11 p.m. across time zones, including weekends — no decision was blocked for more than 24 hours
• The "daily meeting" model: assign an owner to an urgent problem, expect daily updates, give them unlimited resources except time
• Being in the details meant tracking conversion cell by cell across 500 country/document combinations for KYC — "no user left behind," including one user in Congo
• Extreme ownership works when people are highly compensated, the company is growing fast, and there is genuine mission belief

Career acceleration principles

• Join companies growing fast — learning compounds faster at high-growth companies, just like compound interest
• Optimize for your strengths, not your weaknesses; find roles where your superpowers determine success
• Do not optimize for compensation early in your career — the majority of lifetime earnings are back-loaded
• Decide early whether you genuinely want a C-suite path; if you have to weigh work-life balance, the answer is probably no
• Alternative paths: founding a company, building deep domain expertise (e.g., KYC, fraud, card schemes), or building a full life where work is one part among many

Discovering your strengths

• Strengths Finder 2.0 (now CliftonStrengths) is a practical starting point
• Agoda paid $5,000 per PM hire for a six-hour psychometric assessment measuring IQ across dimensions plus a four-quadrant dominance/warmth model
• Ray Dalio's strengths tool adds a second layer: how you rate yourself vs. how your team rates you — overlap reveals true strengths
• Simpler method: notice which parts of your PM work you find energising and easy vs. draining and hard; seek roles that weight the former

Product strategy and experimentation

• Strategy is overrated for most PMs — "how fast can I go from hypothesis to data" is a better frame
• The moment you build experimentation, you make product management scientific; you can rebut any stakeholder's opinion with evidence
• Use experimentation tools (e.g., Statsig) to run structured tests; look at experiments, p-values, and how quickly you reach statistical significance
• Cohort-level analysis is essential — aggregate data mixes users of wildly different vintages and produces bad decisions
• Reserve deep pre-work for irreversible decisions or situations where test results take too long to arrive

High-leverage focus and founder mode

• Work on problems with a 10x positive or negative impact — for most growth companies, that's either growth or compliance
• Alex Algard (White Pages) physically moved his desk to whichever department had the highest-leverage problem until it was solved
• CZ at Binance would take on specific product areas himself; his PMs felt safe saying no to him because they owned the domain
• A full calendar is a badge of shame: you cannot find high-leverage problems if every hour is booked
• Humility is required — "this is beneath me" thinking prevents leaders from being where the real work is

Geography and career geography

• Early career: West Coast US is the best place for tech density, networks, and brand-building; alternatives include Bangalore for India, Dubai for crypto, London/Singapore for finance
• Non-US companies that are dominant in their local market (N26, Revolut, Intercom in Ireland) attract top regional talent and produce strong PMs by the same mechanism as Bay Area companies
• FinTech specifically trains PMs in existential trade-offs — every decision can be company-ending — producing stronger stakeholder management and risk thinking
• Compensation is lower outside the US; if you accept that and play to long-term compounding, the trade-off is worth it
• Career ceiling risk: as you advance, your next role may require relocating again; plan for geographic flexibility or accept a ceiling

Failure: Google Hangouts

• Was the first PM on Hangouts — thousands of people, full Google resources, Larry Page's direct support — and still failed to build a great messaging product
• Lesson: certain products are incompatible with a company's DNA (Google with social, Microsoft with mobile, Facebook with enterprise)
• Lesson: avoid projects with 6–12 month timelines before you get signal — macro forces (regulation, COVID, market crashes) will move faster than your roadmap
• The Hangouts team did invent WebRTC, which now underpins every video call in the world — a massive technical win from a product failure

AI in product

• Coding productivity (co-pilot integrated with repos): ~18–25% developer productivity gain
• Customer support: LLM bots deflecting 60–70% of routine queries
• Fraud detection: pattern recognition on user language and behaviour, especially in peer-to-peer crypto contexts
• Personal CPO use: still searching for a genuine game-changer; most AI writing tools just expand small inputs into large outputs that then need summarising again