Early last year I wrote a bit about some of the ideas I was most interested in learning about and exploring. Now I want to refresh that exercise with this non-exhaustive list of spaces and problems I’m (still) thinking about.

I hope there’s some value in just putting this out there both to force myself to commit my ideas to paper and hopefully to start some conversations with anyone (interested in) building these kinds of things.

If these are things you also care about or if these wrinkle your brain, I’d love to hear from you.

Financial services for bottom 50%

Most Americans are not in good financial shape. We know this. We know that 40% of Americans can’t afford a $400 unexpected expense and that household debt is higher than ever. Yet, for the most part, the “solutions” startups keep proposing don’t make basic sense. For people making $35k a year with $40k in debt, managing their finances is not an optimization problem. You can’t engineer your way to financial security by skimming dollars here and there if the inputs are just insufficient.  We’re not going to solve a consumer debt crisis with more consumer debt and predatory loans, no matter how pretty the packaging.

The only way to fix the problem is to actually transfer wealth and/or increase income. I see a ton of potential for companies that can help people file for bankruptcy (especially student loans), reduce predatory fees, and, most importantly, increase their income through either job training/switching, better negotiating, or even collective bargaining.

Homeownership/building equity

How do we protect communities and let the longtime residents not just avoid being hurt by but actually benefit form development? How can begin to make up for the wealth gap that renter/owner disparities have worsened over the past decade since the global financial crisis?

We need to create better, more accessible paths to building equity and somehow turn renters into owners without just increasing household debt or creating shitty loans for unqualified buyers. This likely means dramatically rethinking what homeownership can look like and most likely divorcing the concepts of house as residence and house as savings account.

Affordable housing

For as long as I’ve been writing anything, I’ve been writing about affordable housing. The housing market is even more punishing for those that aren’t in the market to buy at all (see: building equity above). As cities increasingly become playgrounds for the rich, working people who actually make things run are pushed to the margins. I remain really committed to the idea of co-living, if executed properly, can be a low-cost way to bring new affordable housing stock onto the market. Beyond that, there’s opportunities to lower the cost of new development through pre-fab and other innovative construction methods, to keep putting more downward on brokers, improve public transit and city planning (which has knock-on effects on housing), and so on and so on. 

If we can’t find a solution our housing affordability crisis soon (likely a multitude of solutions from government and the private sector), this will be the defining political and social crisis of the next decade.

Identity and privacy

Cambridge Analytica. Russia hacked the election. Data breaches at Marriott and Target and Equifax and everywhere else. These all get wrapped up into one big flashing red warning light. Now I think there’s beginning to be enough awareness, fear, uncertainty, and doubt about data privacy and security that regular people may be getting the point where they’re willing to pay for it. At this point it seems clear that there’s opportunities for better governance and data/privacy within companies, for users to secure themselves through more private alternatives to traditional technologies and services, and for some whole new paradigm of identity management and how we permission our PII.

Sure VPNs and adblockers and password managers are a good starting place, but when surveillance is the primary operating model of our economy, the change to put users back in control of their own data and safe in their digital lives will have to be profound. We haven’t even begun to scratch the surface on what this can really mean. Whether its better data governance, decentralized identity management, privacy-forward products and services, and/or consumer-friendly cybersecurity tools, I honestly have no idea what this will look like but I’m excited.

Aging

Americans are getting older. Obviously. The portion of (for now) retirement age Americans has already doubled in the past 50 years and could nearly double in the next 30. We’re looking down the barrel of a demographic crisis that will force us to completely re-shape every level of our social organization and challenge its basic operating principles. Some of that is already starting to play out as Baby Boomers come into retirement, often without adequate savings or support. So we’ll need to rethink everything from retirement homes/communities (see co-living above) to how we provide social services to how keep people productive longer and engaged in retirement. How do we export innovations for the young to older generations?

I don’t think we can lump “old people” together into one bucket. Segments have to be understood by cohorts; the elderly and the aging couldn’t be more different. I think I’m generally more interested in the former (new models for healthy, pro-social aging) than in the latter (improvements to convalescent aging/care). Better aging is more a preventative and all-encompassing problem and solution set, as opposed to focusing on the elderly which is largely healthcare-related and corrective.

Climate Change/Resiliency

Ultimately protecting and mitigating the damage from our climate disaster isn’t an individual responsibility. Small consumptive changes aren’t an empty gesture but they also aren’t on the scale we need to be thinking about as a society and a species. Nevertheless there are still important steps to take on the individual level to both improve our carbon footprint and protect ourselves from the ravages of a changing climate. I’m very interested in new approaches to climate-related insurance lines (flood, wildfire, etc.), re-location away from vulnerable areas, and sustainable building techniques and materials (even deconstruction).

It’s deeply problematic that flood and wildfire insurance, for example, require people to rebuild damaged and destroyed homes on the same lots, in the same flood plains and wildfire-prone areas, for example. This is to say nothing of declining utilization of those (federally backed) insurance programs. I’m not an “abandon the coast!” kind of guy but we are going to face migratory pressures within our own borders because of climate change and need to prepare for that. Finally, we need to better build for resiliency and sustainability, both by lowering the outputs of new construction (concrete is a huge contributor to carbon emissions) and by building to better withstand disasters.

These are just the things I’m actively thinking about/pursuing right now. It’s a big world and there’s lots more out there. So tell me what I’m getting wrong, what I’m missing.

2019 was the year that I made a concerted effort to start reading whole books again. In college, it’s relatively easy to lapse as a reader as you struggle to keep up with schoolwork. Entering the work world full time, it’s easy to get sucked into only reading “the trades,” such as they are.

I thought it might be fun to share a bit about what I read this year. Here’s my best attempt at/recollection of chronological order with shout outs to those that recommended each book to me:

Curse of Bigness - Tim Wu

Wu explores anti-trust in the modern economy and tries to lay out a case for a new regulatory and legal regime to promote competition. It’s a quick read and a good primer on the issue but not exactly riveting literature. 

Fifth Risk - Michael Lewis

If you like Michael Lewis you know the drill and you’ll like this. If you’ve never read Michael Lewis, you’ll still probably like series of vignettes on the random parts of our government that handle massively complex tasks and make the world actually work. As usual, Lewis is entertaining and breezy. Given as a gift by my mother.

Ivory Pearl - Jean-Patrick Manchette

Really fun mystery novel set in the ruins of WW2 in Cuba and Europe. In the ultimate cliffhanger, Manchette died before he could finish it. Recommended by Chris and Andy on The Watch podcast.

We Are the Nerds - Christine Lagorio-Chafkin

This in-depth look at the creation and history of Reddit is a good read if you like this sort of thing but it’s just way too long. It would have been better as a longform magazine feature than a 5 page tome. Heard about it from Bradley Tusk.

Snow Crash - Neil Stephenson

Snow Crash is basically The Matrix before The Matrix but way better. It’s got levels, man. At the surface, it’s a cyberpunk mystery adventure. One level down it’s a terrifying picture of a post-internet, late capitalist economy. Beyond that it’s a rich exploration of language and memetic culture and faith. Stephenson is a science fiction maestro and pulls from a tremendous variety of different arenas to build this world and make it feel real. Thanks to Reggie and Christopher Mims for repeatedly pumping this book.

American Gods - Neil Gaiman

Gaiman gets mystical and uses belief in contemporary society along with high fantasy tropes as a vessel to write a hardboiled mystery novel. This book is just a good time. Can’t say the same for the Amazon adaptation. I picked up American Gods in an airport on my way to SF after plowing through Snow Crash much faster than anticipated. Shout out Hudson News!

Gone World - Tom Sweterlitsch

Really killer, thrilling mystery novel in a sci-fi setting. Gone World is super eerie and atmospheric. It follows a detective and she investigates murders across multiple timelines (possible futures and the past), kind of like a near-future version of True Detective with some Minority Report mixed in for good measure. It’s creepy as shit and one of the more compelling time travel mechanics I’ve encountered. Henry Bradley recommended to me and I super strongly endorse it for you. 

Annihilation - Jeff VanderMeer

This short sci-fi horror novel will make you confused and scared of trees. The movie, which got me to read the book, is better.

Severance - Ling Ma

Severance is all about millennials’ sense of loss, listlessness, and regret. It tracks the main character across two timelines - working in publishing in NY and trekking across the US as one of a handful of survivors after a viral epidemic. The virus itself triggers a kind of death by nostalgia and the novel is generally focused on the perils looking backward as felt by the main character, who immigrated from China to the US as a little girl. I was recommended this one by an actor in a creepy face mask as a part of a Verizon commercial that went to air over the summer… So that’s weird.

I was dubbed over though, which hurts.

Super Pumped - Mike Isaac

As I make an effort to not just read books but to read fiction specifically, this one stands out as the one of the only BUSINESS AND TECHNOLOGY books I read in 2019. Though Super Pumped didn’t break any new ground for me, it was kind of crazy to back and revisit Uber’s insanity all at once. It’s easy to forget how much Uber dominated the headlines and for how long. Mike is a great reporter but he’s either not a great writer or the book was just so rushed that he didn’t have the time to be. Super Pumped? More like super formulaic! It deals heavily in great men of history/business tropes and makes a pretty naked effort to force everyone into archetypal characters/arks. Frankly, if you’d enjoy reading it you probably already have.

Seveneves - Neil Stephenson

Remember how much I said I liked Snow Crash? Well Seveneves is even better. Across 600+ pages of techno-babble and minutia, Stephenson chronicles humanity’s race against the clock to launch itself into space in the face of an impending meteorological apocolypse that will render the earth uninhabitable for thousands of years. Where the book really shines however is when he jumps forward 10,000 years forward to humans’ efforts to recolonize the planet. All of the tiny details along the way - the science and engineering and politics that Stephenson lays out in often excruciating detail - become key character elements in the future timeline. Stephenson tracks how these decisions made in moments of crisis ripple out across thousands of years. Everything matters. This is the best book I read this year.

Dancing Bear - James Crumley

This is a fun, hardboiled detective thriller about an environmental conspiracy and drug dealers and Haliburton played out across the mid- and pacific northwest. I still don’t necessarily get what actually happened but the boozing and drugs and sex and sense of danger are a good time. Thanks to Bob Greenlee for giving me this after I complained about leaving my book (the sequel to Annihilation) on the flight to SF.

The Wall - John Lanchester

In The Wall, climate change has made much of the world uninhabitable (sensing a theme yet?). The UK has built a seawall around itself to keep out both the rising seawater and the waves of climate refugees seeking safety. The main characters are soldiers tasked with manning the titular wall and stopping those refugees “the Others” from breaking through. It’s fucking intense and it’s timely. The Wall pairs really nicely with Severance but I think it’s generally better. Like Ling Ma, Lanchester explores the disconnect between parents and children millennials but this time through the prism of climate change and the broken world we are set to inherit. Thanks to Henry Bradley for recommending this one as well. You’re on a roll.

Story of Your Life (and Others) - Ted Chiang

This collection of short science fiction stories runs the gamut of topics and themes. Though the collection is most famous for the titular Story of Your Life, which was adapted into Denis Villeneuve’s Arrival, that wasn’t even one of the standouts (the movie was better). I was going to try to name the standout short stories but found the list would include almost all of them. It’s generally hard to find a single through line but it’s evident that he’s supremely curious. He’s just as compelling on neurology as he is on ad-tech. But I think the stories are at their best when exploring the intersection between science, science fiction, and divinity. It’s well worth your time.

Thanks to Zak Kukoff for telling me about this.

2020

Right now I’m reading a collection of short stories by HP Lovecraft. After that, I plan on revisiting some of the best authors I read in 2019, namely Ted Chiang and Neil Stephenson. There’s a few non-fiction books I want to check out as well including Because Internet and Bob Iger’s The Ride of a Lifetime. I usually have a hard time with BUSINESS books and I read enough tech news as is. Overall, I want to keep sticking mainly to fiction and probably mainly to science fiction within that but I am very open to suggestions now or later.

In a previous post on the value of modeling and how to think about payback, I shared some basic tools and frameworks to approach unit economics and sustainability. 

Now I want to share a follow up that goes into a bit more detail about the tactical decisions that flow from there and start understanding what goes into basic ~~cohort modeling~~.

This is going to build on the content/concepts I covered previously. If you haven’t read Role Modeling or don’t feel like you’re comfortable with these concepts, I’d suggest pausing and checking that out first. Here’s a refresher:

my goal is usually not to determine what will happen, but rather to understand what would need to be true for something to happen. To my mind, the point of modeling is to ask and answer questions rigorously, and to be explicit about your assumptions. Putting things into numbers and breaking processes into discrete steps forces you to be specific in your thinking and with the story you’re telling, even if the numbers and steps are themselves unspecific.

Because startups are money-losing growth machines by design, lots of traditional financial modeling just doesn’t apply. Too often that means overcompensating and looking at top-line performance absent any more rigorous analysis of what I think of as “sustainability.” Is the growth healthy? People throw around all kinds of terms to asses the health and sustainability of startups. I think it’s mostly bullshit and doesn’t capture or describe anything meaningful.

I’ve found myself increasingly creating models (which again are thinking frameworks rather than predictive tools) to blend together all the various top-line figures into a more-startup oriented version of indicative health. I like to think about things in terms of payback in particular.

Once you’ve begun to understand the basic economics of a business, you’ll need to start thinking about more tactical (but no less important) questions using the same general framework. I want to focus on one in particular. What’s the potential impact of an upfront payment versus a pay as you go model? This is obviously crucial to any business with designs on subscription or repeat revenue.

Once again, I’ll use Harry’s and an example and, once again, all these numbers are totally made up and very very wrong. 

Let start with some simple assumptions and say that a full year of Harry’s blades and shaving cream costs you $48 spread across four, quarterly shipments. Let’s also use the same $35 CPA and 70% gross margin we used in the previous payback analysis. The crucial output here is “periods to payback” because it answers what needs to be true. The 7 lifetime orders per customer is then a reasonable assumption that shows out where things net out. Here’s what that got us last time around:

Back to the matter at hand. If you charge people upfront, you’ll probably have fewer customers (asking for more money today is a barrier to purchase). On the other hand, your customers probably won’t churn as much because they’ve already committed to paying (even if you give them a cancellation option or risk free guarantee). Plus, maybe you can charge higher rates for pay as you go. After all, “pay for the year and get 10% off” really just means “pay as you go and I’ll charge you an extra 10%.”

This seems complex enough for now so I’ll put aside the implications on cash flow for the moment. That’s a topic for another time but suffice to say that upfront payment is favorable to you for all the reasons that pay as you go is favorable to your customers.

Reader beware

As I’ve said, the point of this exercise is to answer what needs to be true in order for me to meet my desired outcomes. Everything here is about being rigorous in our thinking, not trying to predict the future. I’m illustrating a general concept, not proving a specific point.

Now let’s use those same assumptions for Harry’s and add in some more info. We’ll assume that Harry’s converts 1.5% of “quality” (non-bounce) visitors to its website into customers. Seems reasonable enough. Some easy back of the envelope math tells us that that means Harry’s is paying $0.53 for each “lead” (person an ad pushes to its site). Finally, we’ll make some simple assumptions around churn/cancellations after each shipment. Here’s what we get:

You might look at this and think the numbers don’t tie. I said it would take 4.17 orders to pay back the CPA, now that only seems like it happens around order 8. What gives?

Unlike the previous Harry’s payback model, this is a time series. That means that churn/retention happens in “real time” as people attrite off with each order rather than all at once at the end. So if you sum up the cohort population percentages through shipment 7 (when net payback starts to get into the black, you’ll get ≈4 orders on average for that cohort. Orders to payback is right in line for the whole population but it takes longer to get there because so many customers churn off far in advance.

(If you couldn’t already tell, this is getting dangerously close to the cohort analysis post I’ve promised.)

Now, putting on our operator hats, we want to know “how do I make this better?” At bare minimum, we’ll want to think through the tradeoffs of an altered model. Everyone seems to offer some kind of “subscribe and save” or “pay now and save” option so there must be something to it. Let’s see what happens.

To be conservative, we’ll say that pay as you go will costs users nothing extra. Churn should go up because customers don’t feel like they’ve already spent the money and conversion should go up because pay as you go is a lower barrier to purchase. We don’t know by how much either will change but we’ll say that both churn and conversion increase by 25% . That gain on conversion decreases CPA because CPL stays the same but now more of those users are actually buying once they hit the site. Otherwise, the inputs are exactly the same. The outcomes, however, vary widely from the first case:

What we see is that even though orders per user over the two year period decreases from 4.37 (paying annually upfront) to 3.77 (pay as you go), net payback more than doubles from 5% to 13% throughout the same timespan.

So obviously this is the right answer, right?

Not necessarily. You have to remember that I’m making some pretty wild assumptions. The devil is in the details and no matter how robust your model and how much data you have, early stage operators need to have conviction behind their choices and a POV that goes beyond 20 minutes of excel. The “right” answer will vary based on factors this type of model couldn’t possibly capture, factors that are intrinsic to your customers and your product and your brand and your cash flow needs and your goals.

But this is at least a good place to start.

For anyone who’s interested, I’ve updated the payback model in Google Sheets to include this exercise. Play around with it, let me know what I got wrong, and tell me what I should be thinking about next.

I get a lot of people asking me how to get into venture capital. How did I get my job? What’s my story? Who’s hiring? What are funds looking for? Is Tusk hiring? Most weeks, I speak to one or two people looking to work in VC, usually for analyst/associate roles.

Most or all of them seem well intentioned, smart, and eager to contribute. I want to help them but we’re not hiring so the best I can do is offer whatever insight I have.

I tend to give them all some version of the same advice/feedback and thought it might be good to write this down for anyone else looking to work in venture capital.

The short answer is that, under generic terms, you shouldn’t. It’s not a good goal, won’t make you happy, and isn’t the thing you think you’re applying for. Here’s why.

1) It’s very hard to get a job in VC.

Capital scales very efficiently against labor. The number of people it takes to invest $100 million is not meaningfully different than the number of people it takes to invest $500 million. Consequently, venture capital funds don’t need to hire at the same pace as the startups they invest in and they don’t generally hire on any particular cycle (at least not one that will be familiar to bankers and consultants).

The VC hiring process is opaque and takes a long time. The job openings are rarely publicized and the competition is intense. Hiring is usually fairly ad hoc and opportunistic. There might not be a job opening at all until someone meets the right person and decides to hire them without a process.

Even when a process seems more accessible and has an open listing, VC is, for better and for worse, a connections-driven industry and the recruiting is no exception. As an applicant you need to maximize your surface area: constantly scouring the earth to get meetings and intel and contacts until you manage to be in the right place at the right time to even find someone hiring.

Taken together, it can often take 6+ months of work for even the most credentialed/qualified-seeming people to land a job in VC.

But even if you can wait that long and do land a job…

2) Most of the jobs are not good.

From the outside, people tend to think that being an associate at a venture fund is mostly about running up an expense account, tweeting, and going to parties. You get to play real life Shark Tank and build companies hand in hand with founders! But all of that is fairly incidental to actually doing the job. In many if not most firms, associates and analysts are glorified assistants. Their primary job is volume sourcing to get meetings on partners’ calendars and then doing diligence on partners’ deals (read: papering those investment decisions ex post facto). This is especially true of some of the larger growth-equity style funds that might have hiring processes that look more similar to a bank’s (cyclical, multiple openings at once, etc.).

Because of the aforementioned scaling relationship between capital and labor, venture capitals firms don’t need to add new partners very often. Most junior roles tend to be 2-3 year appointments with limited room for upward mobility. Given that you’re not going to be sticking around, what incentive does anyone have to mentor/invest in you? That’s compounded by the economic structure of venture firms, where carried interest (keeping a portion of the profits from investments) is a finite, rivalrous good. The more carry you have, the less I can have.

But even if you can wait a long time, do land a job, that job gives you room to grow, and you manage to wring some carry out of the partners…

3) You won’t make as much money as you think you will.

I’ve said this before but it bears repeating: almost no one makes money in venture capital, at least not off of performance (getting fat on management fees doesn’t count).  Benchmark returns are really pretty shit. The generic venture fund is worse than public markets but with no liquidity.

Venture capital is famous for following power laws whereby a very small fraction of investments (and by extension a small fraction of funds) produce most of the profits for the whole asset class. So if you’re getting carry in a generic/random fund, the returns just aren’t very good.

If it’s the salary you care about, you can make the same or more in banking or consulting, or in a business role at a later stage/pre-IPO company.

“But, Yoni,” you say, “you work in venture. Is your job terrible?”

I am very lucky.

I have a great job that does not conform to most of what I’ve described above. I came into a very unique situation, mostly through sheer luck. My experience has been so predicated on being in the right place at the right time that it’s really not repeatable/replicable. It’s almost not worth going into. Most of my analyst/associate friends in good situations at other firms also got their jobs through similarly non-replicable paths.

And if/when I leave Tusk, it won’t be to go work at another venture fund.

So don’t fall victim to survivorship bias. It’s only the people who are lucky enough to have figured out/landed in a really good situation that are left around to be asked advice.

So what should you do?

Look, if you’ve made it this far, you must have a pretty high tolerance for my sage wisdom. Why should I tone it down now?

Take a step back and ask yourself why you want to work in VC. Then think seriously about where/how else you might be able to scratch that same itch in another job.

Maybe you want to do strategic thinking and problem solving in biz ops, growth, or strategy at a late stage company. Maybe you should spend time as a really analytical thinker in private equity. Maybe you want broad experience juggling many balls in an ops role or as a chief of staff at an early stage company. Maybe you should go to business school for the network/community you’re trying to build (or maybe you should just start tweeting more - seriously). Maybe you love jet-setting around and doing meetings and making DEALS and sales could be the right place for you.

The list goes on and on. And maybe you’re ok with doing VC for a couple years and don’t want/need to have a shot at a partner-track position. That’s fine too, so long as you can be clear-eyed going into it.

No matter what the answer is, you have to separate out the “job to be done” from the the job you think you want.

IF you are going to work in venture, try to optimize for partner/fund rather than generic “venture capital.” As I’ve said, most jobs and funds are bad. The biggest brand name funds are functionally impossible to get hired at and working there is unlikely to be any better than what I’ve described above. I’d suggest going to a new fund where you stand a better shot at having upward mobility, economic upside (carry), and the ability to drive outcomes.

Now I know that this is somewhat of a controversial stance. Smart people that I respect have said it’s better go for a brand name and use that to pivot elsewhere where you can have that better job eventually; it’s easier to move downstream that upstream. My preference/bias is to bet on myself and new funds are extremely high risk/reward. Knowing that most venture funds, like most startups, won’t succeed/produce great outcomes, I’d at least rather have the potential for upside. So you need to have a clear sense of where you stand on these questions and accept the tradeoffs that come either way.

I don’t say any of this to discourage you or make you feel shitty. I’m saying this because I’ve seen enough people go through really long, painful process before they come to see what I’m saying here and I love you.

And if you take my advice and I’m completely wrong about everything, at least you’ll be more sure of what you already knew. A little bit of introspection and self-knowledge never hurt anyone.

Couple of things before I get into this. First, none of this is investment advice. I’m an idiot and you really, really shouldn’t listen to my opinions. Second, if you hold me accountable to any of this then the joke’s really on you, bro.

Now let me spit some facts.

The Federal Reserve estimates that 31% of all the US dollar bills in circulation today are $100 bills. This is a 20% from 15 years ago. (US Fed)

80% of all US $100 bills are held overseas, according to the Chicago Fed Board, up from 15-30% in 1980. (Chicago Fed)

Looking at the total US dollar bill circulation, that means that $100 bills stored overseas accounts for ≈64% of the total value of printed US currency. This represents a hair (few hundred million dollars) over one trillion dollars in value (that’s $1,000,000,000,000 or one thousand billions of dollars) sitting in $100-denominated bills parked overseas.

Why are people keeping hordes of $100 bills overseas? Lots of reasons. I’d guess mostly to do with crime on one hand and local economic instability on the other. $100 bills are obviously the most efficient way to store, transport, and transact in cash that you want to keep out of the regular financial system. $100 bills take up the least space, are universally accepted, and are well made enough to keep their integrity for years.

But crypto-assets are better than physical bills on each and every count.

So that $1 trillion in $100-denominated bills stored overseas? That’s the baseline price target for Bitcoin’s market cap. The max number of Bitcoins that can be mined is 21 million. So assuming none get lost (1/4-1/2 probably have been), that sets a price target for Bitcoin at ≈$51,000 before accounting for any other use cases beyond displacing $100 bills as a store of value overseas.

I think Bitcoin will be very price volatile but generally trend upwards until reaching something within spitting distance of that price point and then become relatively price stable for the future. And I think it’ll be Bitcoin specifically (rather than say Monero) because it has the biggest headstart and most “brand recognition” among all crypto-assets, not unlike the US dollar relative to other fiat currencies. To put it in perspective, Bitcoin makes up about 65% of the total crypto-asset market cap, depending on the day. 

I’m gonna be buying and HODLing all the way to $51k.

My DMs are open for any hedge funds that want me to come in and run things from now on.

You’re welcome.