Tag: investing

The Dollars and Cents of Moving On

I just lived through a lesson I set in motion over the past two decades, and I think it is worth writing down while it is fresh: how you structure retirement money, and what happens when the structure you picked meets the exit you actually take.

How the money actually arrives

Start with the standard ways a company pays you. Base salary. Bonus. Many companies add stock: incentive plans, employee stock purchase plans. And then there is the leverage layer on top: retirement accounts, and for some of us, deferred compensation.

Deferred comp is a simple premise. Take some of today’s dollars, put them into investments pre-tax, let them grow, and have them paid back to you in the future, when you are theoretically in a lower tax bracket. That last part is key to the whole concept. And you choose the schedule for that payback: all of it when you leave the company, staggered in multiple ways, on a specific date, or any combination.  And you typically reset those payback parameters at each years renewal.

Here is the catch. There is no guidance on how to make that choice. Unless you go talk to a financial analyst, and many of us either don’t have access, choose not to, or don’t believe they have our best interests in mind, you work it out on your own. Your employer won’t take on the liability of giving you guidance, so that’s not an option. So you make a decision with the best information you have, which is close to none, because the decision is about an ending you cannot see yet.

The choice you make blind

Here is what I picked, as an example. Some of my deferred comp pays out over five years starting at termination. Some pays out over ten. I did not have any structure or thinking in mind beyond one instinct: it didn’t seem right that I would retire and all of the sudden need all of that money. If this is supposed to be a tax optimization strategy, taking it all at once defeats the point. So: five-year and ten-year streams, starting right after I leave, seemed like a good model.  And honestly, the difference between five-year and ten-year payouts was more because I couldn’t remember what I had done the year before rather than anything intentional

It’s all kind of a crapshoot, because you don’t actually know any of the key facts when you are setting it up. You don’t know the year you will leave the employer, let alone the month.  You don’t know if you’ll be moving to a new job or retiring or desperately hunting for a job.  And you don’t know what events cause you to leave the job, and if those events carry financial needs or impacts.  It turns out, all of this does matter.

The year everything paid out at once

I left Microsoft in September. Here’s an example to think through.

Eight and a half months of salary, because most of the year was already worked. A severance payment, landing after the last day. The annual bonus, if you are smart enough to time separation right after the qualification date. Then in October, the deferred compensation starts, all streams, per the schedules I set up over the past two decades.

What this means for me is that between September and October, I am collecting more paychecks than I would in a standard working year. This impacts taxes and tax brackets.  Next year will be, at least at this point, significantly lower. Which is backwards from concept of deferred comp.

Let me be careful here, because this is totally a first-world problem. A lot of people right now are worried about their jobs, their families, and how to pay for groceries, and “my payouts stacked up” is not a hardship. It is definitely better than not getting paid, or getting paid less than your worth. But the mechanics are worth understanding precisely because nobody explains them to you when the choices are in front of you.

Had I known the ending back when I set this up, I would have structured it differently: deferred comp starting at termination plus four to six months, which would have pushed those streams into the lower-bracket year. Or I could have slid my last day to January and let everything land in the next calendar year. And knowing that a September exit is actually the natural shape for a lot of careers, since it sits right after the bonus and rewards cycle, I could have guessed better than I did.

But I will take the tax burden as the price of the extra three or four months of not having to work. I am happy with the date. And there is an honest counterweight to all this second-guessing: you might not leave on your own terms. If you get walked out in a layoff, having your deferred comp start immediately might be exactly the right structure. The schedule that is tax-inefficient for a planned retirement could be a lifeline for an unplanned one. You are choosing blind for both cases at once.

Every October for the next decade

One more artifact of that decades-old choice: some of my deferred comp pays out at the start of October, every October, for the next ten years. It is not a huge amount of money. But there it is, a small annual deposit from a decision made in a different life, arriving like a letter I mailed to myself from a lifetime ago.

The Gary problem

Two other cases to consider.

A friend of mine is working out his retirement date right now, and he has close to 100% of his salary going into deferred comp. For him, the month or quarter he picks genuinely matters. The structure is intentional.

And then there is my old buddy Gary. Years ago, Gary was convinced he would retire at 45 because he and his wife were living cheap and saving hard, which is a wonderful idea. But they almost exclusively poured that savings into their 401ks. Retirement accounts are not penalty-free until 59 and a half (the IRS rule), and the main exception, the Rule of 55, only opens your current employer’s 401k if you keep working there into the year you turn 55. Retire at 45 with everything in a 401k and you have built a nest egg you can watch compound for fourteen years and cannot spend. Hey bud, what exactly is the plan for years one through fourteen?

The pattern

Zoom out and there is a whole matrix here: Roth and standard retirement accounts, deferred comp, standard comp, severance, bonus, stock awards and grants. When each one pays, what each one costs in taxes, how centralized or diversified the whole picture is. Every one of those is a choice you make years before you know the story you are choosing for, and they all come together in the same few months at the end.

I made my choices with the best information I had at the time, and I am living with repercussions that are, honestly, pretty gentle. But the pattern deserves better than hope. None of this is advice; it is scar tissue with a structure in it, and the structure is worth mapping before your own October comes around.  So put some thought into the following: (1) how and when your retirement accounts pay out, (2) how and when, across the tax year, you would optimally control your retirement date, (3) what your immediate versus delayed plans are for what you are going to do once you leave your job.

I’m no expert, but for people that are making decisions now from the other side of the equation I’m happy to have a conversation about what I would do the same, and what I might do different.

The Oldest Trade in the World Is Coming for Compute

Thanks to Makoto Eyre I’ve been reading The World for Sale, the Javier Blas and Jack Farchy book about the commodity trading houses. It confirms one of my core beliefs: the most reliable way to make money is inequality of information.

Think about how traders actually make their money. I know something about the wheat harvest in the Americas that you do not, because I did more research, or I bought better satellite imagery, or I have people on the ground. So I buy or sell the futures and take the spread between what I know and what the market knows. Oil was the giant version of this: a huge boom in demand layered over massive inequality in supply, demand, market access, and even basic knowledge of who had what kind of crude where. The traders who closed those information gaps, one contract at a time, made billions doing it.

Here is the thing though. My drive in understanding this is not to recreate the commodity traders’ billions. Technically, I wouldn’t turn that down, but okay, whatever. My drive is the opposite trade: find where the inefficiencies of the market are, because if you can balance the inequality of information, if more people can see what only the traders used to see, the frictional cost that gets skimmed off every transaction shrinks. And when the friction disappears, the end product gets cheaper. That is the whole arc: equal information leads to efficient markets leads to cheaper everything. The traders monetize the gap, and the consumers pay.

The newest inefficient market

Hold that principle and look at AI.

The demand explosion is not one market, it is a whole stack of them: compute itself, the chips that produce it, the racks and components that fill the data centers, the data centers themselves, the interconnect that ties them together, and the power that feeds all of it. Every layer of that stack is running hot with demand, and every layer is full of exactly the kind of information inequality the commodity traders would recognize from a hundred yards away. Who has capacity, who needs it, what an H100 hour actually clears at today versus what you are quoted: that spread is where the friction lives.

So the natural question becomes: does this stack get commoditized, and who builds the market?

It’s already happening

That question walked straight into an episode of the Moonshots podcast I was listening to (episode 278), which features Kush Bavaria, the 23-year-old co-founder and CEO of a company called Ornn. What Ornn is building is the infrastructure to trade AI compute as a commodity: live price indices across the GPU rental market, tracking what an hour of H100 or B200 actually costs, and the financial plumbing on top.

It is live today, in an early form. You can already take positions on GPU compute prices on Kalshi against Ornn’s index, though honestly the market there is thin: you can bet where the price of GPU compute lands at the end of a month, but there is no real futures market yet, no serious hedging instrument. That is coming. Ornn is working on cleared compute futures with Intercontinental Exchange, and Kalshi’s own CEO is now calling compute “the new oil” and racing to build the forward curve.

Sit with the shape of that for a second. The book on my nightstand is about the last century’s masters of information inequality. The podcast in my ears is about this decade’s attempt to build the exchange where compute trades like wheat. My brain went immediately to the space between them.

Steeper than oil

Here is the part that has my attention. Go look at oil’s actual price history. In 1970, a barrel went for about three dollars. The 1973 embargo quadrupled it to twelve in a matter of months, and the world treated that as a full-blown crisis. By 1980 it had touched the mid thirties, and $25 oil, a number that would have been unheard of a decade earlier, was suddenly the floor. Then in 2008 it spiked to $147, and has never looked back. This spring it spiked to $120, and today it trades near ninety: three and a half times that unheard-of number, and almost thirty times over what for years was “normal”. That is what it looks like when a demand curve outruns the market’s ability to organize supply.

My big takeaway: the demand curve for compute is accelerating faster than the demand for oil ever did. Oil demand grew with economies and new industries, a few percent a year, and still produced shocks. Compute demand compounds with the AI buildout itself. Every model generation, every data center, every agent deployment adds load, and the buildout is speeding up, not settling. By January we’ll be seeing a new model release every day. The price signal is already twitchy in a way oil took decades to become: an hour of B200 compute peaked at $6.11 at the end of May and traded at $4.22 three weeks later, a 31 percent move in under a month. Oil needed an embargo to move like that. Compute did it in a normal June.

A market with that demand curve, that volatility, and no futures curve yet is the purest information-inequality setup since the tanker traders of the seventies. The people with better information about capacity, load, and power are going to take trader profits out of it. Which is exactly why the equalizing infrastructure, the public price, the index, the forward curve, matters more here than it ever did for oil. The steeper the demand curve, the bigger the frictional cost of unequal information, and the bigger the payoff for everyone downstream when that information gets equalized.