How well do startups pay PMs in terms of equity compensation?

Have there ever been IPO millionaires for PMs?
We hear startup software engineers making a lot of money from IPOs. Does the same thing happen for PMs? Any personal experience or anecdotes from friends in the industry


I’m a PM working for a VC fund’s AI investment engine (my hopeful exit will be to a Series B startup that my AI finds! lol- probably as a Sr. PM or Director one day).

  1. If you go for a Series B company, then equity could be worth millions in a few years BUT I would check to see if most of the below is true before taking a product role.
  2. revenue is >$6 million
  3. revenue growth is at least 100% per year
  4. NDR AND GDR >110%
  5. Product led growth (I find these companies grow the bloody fastest when they hit true Product-market fit)
  6. retention should be high (depends on which market vertical they operate in, customers etc.)
  7. It is possible to make millions without joining startups- even beyond FAANG. Some funds will pay carry worth 7 figures with every fund they raise but the payout is after 7-10 years (the fund has to pay out their investors first).

Early startup shares very rarely worth anything other than 0. Not to say it doesn’t happen, people win on gambling and lottery too, but I wouldn’t include it in my planning. A surer bet than aiming for startup millionaire is FAANG stock comp, that does end up in your pocket and makes a difference.


Agree here. Scope for scope, a FAANG, or more accurately F/N/G will on average pay more.

A Senior PM at a Series C will probably make $175k base, and let’s just pretend have options that are worth enough to be 7figures on a good exit. Approx 1/10 series C will survive for those shares to be worth something. And let’s say 50% will strike it rich. So, 5% Chance of those shares being worth $1m-$10 in the next 5 years. That’s an expected value of 50k-$500k. So, let’s use the high end. That gives a 5-year expected compensation of $1.375m over those 5 years or an average of $275k/yr.

In terms of scope and size, that is probably equivalent to an L5/6 at Facebook/Google. Let’s assume L5. A low end L5 comp package here is 325k/year. But you’ll see stock growth as well, plus refreshers, plus promos. Those same 5 years you’re likely to see well north of $2m comp, and if you’re good, you can go from L5 to L8 in that time period and be rolling over 7 figures per year consistently.


FAANG companies are generous. Most people take 5+ years to go from level 5 to level 6 and often longer, and it’s very rare to get promoted past level 6. You said “good” but it’s more like top tier in a company of already extremely top tier talent. You’re also projecting the bull market to continue for tech, and if so the VC bubble/IPO bull market should be even stronger.


As per my Meta PM contacts, FB’s median (50% at or above) PM is Level 6, which is ~500k TC, at 25%, L7- $750K, 10% - D1+ ($1m>). They publish the level breakdown internally.


@AngelaBlue, your equation is predicated on the assumption that startups at Series C all have an equally likely chance of success, which is completely and utterly wrong.

Uber raised a nearly $300M Series C in 2013. If you picked 9 other random Series C companies from that year out of a hat and Uber and presented those options to 100 engineers and PMs in 2013 there would be a massively skewed distribution in favor of Uber because there was a large number of qualitative and quantitive signals of success including the fact they had close to a $4B valuation which is at minimum a strong vote of investor confidence.

You could also look at who was running the business, the quality of engineers and the leadership team, the growth rates, etc.

My point is that using expected value in this situation is nonsensical because the assumption that random chance plays a significant part in the success of a business at the Series C plus level is not true.


@NaomiNwosu, It’s not nonsensical inherently. It is of course skewed. I was just keeping math simplistic. Like others have said, higher risk, higher reward. And, you can mitigate that risk based on a number of factors.

But if you go to Uber at Series C with a unicorn valuation already in place, your 100X chances go down even further, if not eliminate, vs a company with a Series C valuation of 100M.

You’re right that’s its not simple. You can definitely optimize the startup world.

but for myself, I’ll chill out in FAANG, and enjoy my broad scope, and steady paycheck. I have a family, and the stability is worth it, and on average is worth more overall.


@AngelaBlue, It is nonsensical to the point - which the OP of the thread made that was also nonsensical. Startups are not like gambling, anymore than investing is like gambling. And the only people who think investing is like gambling, are people who don’t understand investing.

It’s fine if you want to take the least risky road, but it’s irritating when folks use a silly expected value equation to justify staying at FAANG for 20 years. They are both fine options for different types of people.


I don’t think so. Expected value is a common investing/OpEx thought process. Besides, I don’t need 20 years at a FAANG for FI. 10 years in FAANG product should be enough to accumulate $4+m.


It doesn’t make much sense in this context whether it’s widely used or not. It simply does not work.

Cumulative? Sure, that’s pretty easy. $4M in free cash flow? No, pretty unlikely unless you’re a rockstar or came into the company quite senior already.


This is so silly. No offense - but the idea that early startup shares are all equal (0) and the likelihood of picking a ‘winner’ is no different from winning the lottery or gambling is completely and utterly wrong. As an example, I know folks who have bounced from start-up to start-up after an exit event and have a 100% hit-rate. I mean even certain VCs like Sequoia have something like 50% hit-rates. Saying that shares are all the same would invalidate what top investment firms do. If you’re going to work for an early startup, which I consider anything earlier than Series D, there are some pretty simple tricks you can use to pick winners with a relatively high degree of certainty and make far more money in the same time span as you would in FAANG.

Of course there’s some level of risk, hence the greater reward, but the idea it’s totally random is just ridiculous.


Would you mind elaborating on the “pretty simple tricks”? Currently at a larger company and satisfied with my cash comp, but not knowing how to pick winning startups is one of the reasons I haven’t looked much into them.



  1. Funding: Who are they funded by and how much. There are tiers to VCs in the same way there are tiers to startups. Something like Amplify, Sequoia, Redpoint, Greylock, have very high ‘win’ rates but there are other startups (younger ones with specialized portfolios) with even higher, in some cases 75%+. Most of this information is available through Crunchbase, but you can also just ask. I recommend asking to speak directly to the VCs if you are really early, and also speaking to big VCs that AREN’T backing them. The ideal response to the question ‘why didn’t you fund them?’ is ‘We tried’ and not ‘we think there is a fundamental flaw to the business model’ or ‘a competitor is better’ (although the latter is encouraging also - it means the product area isa. good one) Also, be sure to look at who funded each round. Ideally, it’s the same VC from preseed to the current state. A great startup will get big early adopters and VCs will try to get the majority of each term sheet every round.
  2. Team: Cohorts of teams have much higher success ratios than others. For example, teams out of hypergrowth startups that have achieved IPO success like Airbnb, Uber, Coinbase, Snowflake, do very well when it comes to acquisitions and exits, especially if the teams is building off open-source technology, they themselves invented. That’s because A.) they know how to build really good technology very quickly B.) they’ve ideally built the startup in question or something similar already, so they know most of the hurdles and traps, C.) there’s not a hiring which often happens in business teams unfamiliar with product or vice versa.
  3. CEO: One of the biggest screens is who the CEO is. Make sure you meet with them directly, if it’s earlier than C. I typically only advocate working for CEOs with product and engineering experience: that means former PMs, designers, engineers, or data scientists with years of experience ideally in management - builders basically who understand how to find product market fit and also how to hire and structure a team. If the CEO is say a businessperson with 40 years’ experience, or a engineer straight out of college, I’d avoid as those are pretty risky.
  4. Thought Leadership: The reason thought leadership is important is because it demonstrates the business understands the power of brand, and if they understand brand, it means they understand marketing. Questions to ask: Are they holding conferences? Does everyone in the industry know them as the ‘new kid on the block?’ Are bigger legacy companies afraid of them? You can figure out all this through pretty simple internet searches but also talking to people. I recommend asking to meet with the company’s advisors and ask them honest questions. Send an email to a competitor or a few customers and say: ‘hey have you heard of X before?’ Another way is to see who’s driving the chatter around your area online. Is it your company or someone else?
  5. Customers: This is an obvious one, but normally a business won’t tell you who they are working with due to confidentiality agreements, but you can learn how many deals, the rough deal size, the volume of new deals, and the main competitors to those deals if B2B and raw volume if B2C. You’re looking for an increasing speed of deals over time, and larger deal sizes over time. It’s about the rate of improvement. A proxy for this can be funding rounds. Ask them to explain why they went for the amount they did in each round and ideally the answer is: ‘we’re scaling, and we needed more infra / support / sales whatever.’
  6. Clear path towards profitability: This is one fairly obvious and you just need to ask about it and ensure that it exists. ‘we’ll figure that out eventually’ is not the answer you want to hear, nor do you want some abstract explanation. The best answer is something tangible with cost centers that’s scale with the business. You have to use some judgement here.
  7. Caliber of People who have joined: Look at the other employees who have joined on LinkedIn. Are these A players? People and managers from big name companies that gave up huge salaries. Or are they from nothing burger companies that maybe even got a pay bump, want to be in the valley, or are trying to strike it big? If it’s the former, great sign. It’s one of the best types of social proof. If it’s the latter, red flag.
  8. Turnover: Are people quitting or are people staying a long time from the beginning? You can generally get all this data on LinkedIn as well, definitely through the Sales explorer. You do NOT want to go to a company with 15 hires that has lost 5 in the last month.

So I could go on, but that’s just a few things I personally look at for when making a startup jump. It’s not about any one category, but the multitude of all these things put together that gives you something like this:

A startup funded by a top tier VC, where other VCs are sad they missed out, run by either previous startup founders or top product engineering folks from a former hypergrowth startup, ideally built on a focus area they understand well and have developed software for before, with a strong technical or product focused CEO, they are known in the space even amongst a niche as a disruptor and competitor, and ideally are at least present when customers are considering competitors, there is good customer growth, a clear path towards profitability (or a good explanation on how to get there), top tier people from the technical and business side who are joining, and low if not non-existent turnover.

The majority of those things you can get through interview or is available online, and some may require digging through contacting people. In my experience as an investor the success rates of those companies in pre-seed / seed / A is greater than 50%, in B above 75%, in C above 90%, in D nearly 100%.

Good luck!


@NathanEndicott, Phenomenal post, thanks for sharing. The only thing I can’t square with is the success rate. Do top VCs really have 50%+ success rate? That’s not in line with what I heard anecdotally, one hit out of ten is supposed to be crazy good I thought. I do agree that at growth stage (C and later) it becomes much more reliable.


“Simple tricks”. Sounds like an infomercial. :smile:


I’m guessing @NathanEndicott meant things like looking at what VCs (and what VC partners) are involved, whether a VC firm has followed from one round to the next (very promising), how much funding the company is receiving and their expected margins (a software company will have very high margins whereas a hardware or biotech will not), the long-term vision and its feasibility, looking at recent hires especially among leadership.

Plus, just logic. It wasn’t hard to guess that AirBnB would IPO. Even in the mid 2010-s Google was matching competing offers from them and similar companies (meaning treated their private equity as equivalent to GOOG public stock).

A more recent example might be Dapper Labs. In April they raised at 2.6 billion. A few weeks later they were already looking at next round and in September they raised at 7.8 billion. Your comp tripled in just a few months. The speed was surprising, but anyone who was plugged into crypto knew the company was on a rocket ship.


@NathanEndicott, I’ll caveat - senior managers, the top product management role at the company, can certainly do what you say. But for everyone else my experience is employee stock comp is negligible by the time you have enough data to be able to bet on whether the company will be a success or not. I’m sharing a London/EU experience for context here.


Again, not true at all. I have worked for multiple startups.

I came into my last startup as a Senior PM, which was equivalent to a Microsoft L63. My initial equity grant was 40K options at Series C which at strike price I left put me well into the millions. Within a year of working there I had close to double the options to 70K and was in line for much more. That company is currently on its Series E and I know internally they are working on an IPO. I specifically chose that company, among several other offers I turned down. It was not random.

The company I am out now I joined at the Series D as Principal PM with 80K options, which are also worth well into the millions.

I know many other people who have gotten similar or even better deals. One of my best friends was an entry level salesperson at a B2B Infrastructure startup and got a $700K payout after a year, then joined CircleCI in their A and got around 30K options, then joined LaunchDarkly after two years and got 50K, and now is with another high growth startup as an AE with even more. All 3 of the startups he joined are going to exit - CircleCI and LD are both unicorns. He’ll make $10M+ over the next 5 years or so and he’s not even 30. He did that by understanding the market, talking to customers, and being very purposeful in where he went.

Don’t take this the wrong way, but I think there is just another level of startup hopping and planning I don’t think you’re familiar with. So sure, to someone without that experience it does seem totally random. I’m almost 100% positive people are doing this in London/EU as well.


You may make a lot of money (hope you do) but this is not necessarily a guarantee. 1) Many unicorns are overvalued, and IPOs do get delayed. 2) Even if the company goes IPO, as a rank-and-file employee there will be a lock up period before you can cash out. A lot can happen. Stocks can pop and then fizzle fast.

I started working in the late Dot Com 1.0 years. I had several friends who were worth millions on paper one quarter after their company went public only to see their stock worthless 6 months later.