Specifically, when you have kids. And whether you’re walking into it with a Trad Wife, as a dual-income power couple, or Daddy Day Care holding down the fort.

Full disclosure, I loved my twenties. Had Jack’s books existed then, it would have added some nice perspective that I’m sure would have been useful. Not because I messed up, but because opportunity costs aren’t obvious, especially at that age.

The “Later” Problem

Here’s an inflection point I’ve seen play out repeatedly: “I’m going to optimize really hard, really early, for the life I want.” What I typically find this translates to is: I’m going to hustle my ass off now so I can chill later.”

The catch? So many people have a different perception of what later means. And when that time horizon stretches further than anticipated, disillusionment sets in. And as a mid-thirties, married dude with two kids, I can tell you: my life would look very different if I were still single with no kids. Would I have more money? I would think so. Would I be wealthier? Maybe on paper.

I recently saw one of Shaan Puri’s controversial takes on X that resonates:

The Millionaire Math Nobody Mentions

Here are some statistics:

Thomas J. Stanley’s research from The Millionaire Next Door found that:

• 92% of millionaires are married

• Only ~2% are divorced

• The average millionaire couple has been married 28 years

• They raise an average of 3 children

• Median age: 57

The average millionaire didn’t go all in on solo optimization, and they typically had kids that complicated their spreadsheets.

Now what’s interesting is this data is a little stale considering when the book was written. Newer surveys from 2024 are showing a shifting landscape:

• Roughly two-thirds of millionaires are married (down from 92%)

• About a quarter are divorced (vs. 2%)

• Just over half actually have children

Either the data is capturing a different slice of wealth (tech bros vs. small business builders), or the old model is cracking. Either way, there’s a pattern: wealth accumulation and family formation are not orthogonal variables. They’re inversely correlated, at least in the short term.

The Trade Off You Can’t Escape

I saw a comment the other day on a Substack post responding to a young guy documenting his investment journey, starting with $120k in a concentrated stock portfolio. The reply:

“I’m 10 years your senior and would be starting today with a fraction of what you’re starting with. I wish I would have started earlier…”

Fair. But here’s what the commenter doesn’t know: Was his tradeoff worth it?

We’re consumed by comparison from influencers, curated feeds, and highlight reels that we forget there is always an opportunity cost. That gets lost when you’re wallowing in self pity about how your life doesn’t look like some curated magic on your feed.

How to Actually Optimize For the Life You Want

When you’re optimizing for one thing on your long list of wants, it typically carries an opportunity cost of something else on your list.

Want to be a millionaire by 35? Totally doable on a certain trajectory. Add marriage, a house with a big yard, three kids, and that timeline starts wobbling. A family can be a capital intensive project, yet according to wealth stats, it’s the way to go.

Think about the divorce economics: post-divorce, women see income declines of 46-50%, men 23-28%. First marriages end in divorce ~40% of the time. And yet, 66% of adults remarry. People bet on love. The single, optimized, hyper-mobile life isn’t as shiny in retrospect as it is in theory.

My Take

I’m not suggesting going all in on the Trad Wife movement, or selling you on the FIRE movement. I’m saying this:

If you’re optimizing for maximum wealth accumulation, you’ll likely sacrifice family flexibility.

If you’re optimizing for family, you’ll likely accept slower wealth growth.

If you try to optimize for both simultaneously, you need extraordinary discipline, luck, or both.

Most people think they’ll figure it out later, but later takes longer than expected.

Bottom line: There’s no perfect trajectory. There’s only the one you choose, and the trade-offs you’re willing to live with.

Choose Wisely!

-Pablo

Professional service firms are starting to adopt an AI stack. Workflows are being re-engineered, client deliverables are starting to be automated, but there is one outstanding problem:

Almost nobody in the application layer has figured out their long-term pricing model.

It feels like we’re operating in a temporary economic window. Venture capital is subsidizing the massive compute and inference costs required to run these models with the intention of buying time. As firms rush to integrate these tools the true economic impact is a grey area. To add another level of complexity, this is all happening while operating margins in the professional services industry leave very little room for error.

The Margin Reality Check

To understand the severity of this risk, you have to understand the underlying economics of professional services.

When you look at the financials of a mid-sized regional player, or a large publicly traded firm, the story is consistent: margins are slim, typically 5% to 10% after producer compensation.

With slim operating margins there’s not a lot of balance sheet flexibility to absorb unexpected capital shocks. If a software vendor powers 40% of your workflow today at $50 per user per month, what happens when that vendor shifts to a heavy usage-based or value-based pricing model in 24 months to reach their own profitability? What happens if that bill triples?

The time that is being bought through VC subsidies is being used to get everyone hooked on an operational “drug” without knowing the long-term price per dose.

Hedging Your Risk

Don’t wait for software vendors to figure out their unit economics. Develop a conservative strategy to insulate your bottom line. Because direct labor is the single largest line item in professional services, your headcount strategy is your primary hedging mechanism.

Path A: Mature/Moderate Growth Firms

If top line growth is steady rather than exponential, efficiency gains from AI must translate into direct headcount reduction. Holding onto excess capacity while paying new AI software bills will guarantee margin erosion. This is also a good test to understand whether or not your AI adoption strategy is working effectively.

If you can’t cut headcount and maintain the status quo at a minimum from a client service perspective, your AI implementation needs more time, energy, and focus.

Path B: Fast Growing Firms

If you are aggressively scaling revenue, you must immediately adjust your hiring-to-revenue ratio. For example:

• Old benchmark: Hire 2 net-new FTEs for every $1M in new account revenue.

• New AI benchmark: Slow hiring to 1 net-new FTE for every $1M in new account revenue.

Who Actually Captures Value?

Private equity is pouring billions into firm consolidation under the assumption that AI will drive margin expansion. But will it?

In professional services, people are the means of production and when control of technology sits in the hands of the producers, extra free cash flow rarely lands entirely on the bottom line. Instead, top talent and high-performing advisors extract that value.

As basic tasks become commoditized, the advisor’s (accountants, attorneys, etc.) role fundamentally shifts:

Old Paradigm: Data entry, and task producers

New Paradigm: AI Director, prompt orchestrator and client advisor

AI will finally kill the hourly billing model

It’s been a long time coming, but it seems that all roads point to the hourly billing model finally being killed as a result of the AI era. When I started Alpine Mar, I was adamant on day 1 that we would not operate off hourly billing. Incentives are not aligned under an hourly billing arrangement, and it doesn’t keep the ultimate goal in focus. It still may take some time for hourly billing to wind down completely, but as more firms adopt a value based or outcome based pricing model, it will force the markets hand.

The point is value is no longer generated by executing compliance work, but by guiding AI, auditing output, and delivering high-trust advice. The highest value any advisor generally brings to the table is in the form of creative thinking. Fortunately, we’re on a clear path to eliminating non-creative friction.

If you’re an executive leader, don’t mistake software vendor subsidies for permanent operational efficiency. Track your adoption, guard your margins, adjust your headcount benchmarks, and treat AI for what it is: an unhedged liability that requires active risk management.

One of the earliest impressions I have of Goldman was the recruiter telling me "We're a flatter organization, and it's a true meritocracy." It definitely sounded cool and my naivete immediately thought "great, I should make Partner by next year given the badass I am." One year later, I had a real fresh perspective.

Over my first six months working in Goldman's Finance Division I had a few ups and many downs. To say it was humbling is an understatement. I learned a lot about Capital Markets fairly quickly, and in hindsight was involved in the reporting of some very influential transactions: the Uber, Spotify, Palantir, and Dropbox IPOs, among others. The technical aspects of what I learned through my time at the firm helped me in my overall development, but the technical skillsets were not the most valuable things that I learned.

After my first couple of weeks I started joining one of the VPs on our team for the daily P&L reporting meeting. For context, less than an hour after market closes, the daily P&L gets read out by each division within the firm (globally) to the senior executive team. It's a very quick, fast-paced meeting that calls out the main drivers to the firm's performance that day. In the first few meetings, I had no idea what was going on other than listening to a bunch of people rattling off what sounded like finance gibberish. Was I intimidated? A little.

I realized I had a lot to learn, and quickly. A little over a month in, it was my time to actually call out the daily P&L for the Investment Banking Division. I butchered it, and I heard about it as soon as I got back in the elevator after leaving the meeting. What happened over the next couple of years was this: I pushed myself to get better, to learn quickly, to ask a lot of questions, and to take a lot of initiative. I was uncomfortable — a lot — but it was great. And it helped me tremendously.

I paid very close attention to the highest performers at the firm and I started to notice something. It wasn't about what they knew that made them top performers. In fact, many of them would probably tell you they weren't very technically competent when it came to accounting and finance at all. What they did well had everything to do with how they spoke, how they wrote, how they carried themselves, how they commanded a room; little to do with numbers and markets at the end of the day.

What I realized over time, and more so in hindsight, was that value accrued to people that could do two things well: understand problems, and communicate very effectively. Warren Buffett reportedly credits much of his success to a Dale Carnegie public speaking course, the diploma is framed and hanging in his office. That didn't surprise me. When I recall my time within the walls of Goldman Sachs, the things I remember having the biggest impact weren't the specific deals or big P&L days. It was all about the people dynamics.

When I was there, I was "learning through my skin." I was subconsciously picking up on the things that made people great, and those things were not the obvious ones that I think most people would point to.

Six years later, I’m running one of the fastest growing accounting firms in the country, with over 70 incredible people on staff. The irony isn’t lost on me — I run an accounting firm, and the most important things I do every day have almost nothing to do with accounting. I hire for communication. I build culture through how I show up in a room. I win clients not on technical merit alone, but on trust built through how we speak and how we listen.

In accounting, retained earnings are the profits a company holds onto — value that accumulates quietly over time rather than gets paid out. Looking back, the Goldman years were exactly that for me. Not the deals, not the prestige, not the brand on a résumé. The retained earnings were the lessons I didn’t even know I was collecting until years later, when I needed them most.

The anecdotal evidence that I’m seeing at Alpine Mar suggests the exact opposite. As AI reduces the cost of production, it exponentially increases the value of judgment. We are seeing a structural shift where the demand for high-level financial oversight is not just growing, but it is migrating up-market.

The Talent Void in Mid-Market Enterprises

For decades, $100 million + enterprises have maintained bloated internal finance and accounting departments. Today, those departments are hollow. There is a measurable shortage of accounting talent, driven by a decade + of “boring” work being undervalued and under-incentivized. This issue has been widely reported over the last decade. In 2022, the WSJ released this article, where a public company CFO shared:

“We have the people, but I don’t think the people we have are necessarily the people that are the most qualified.”

Many organizations have compounded this error by refusing to market these roles at competitive rates, betting on a “technological salvation” that hasn’t arrived. They view accounting as a commodity to be automated rather than a pillar of capital preservation. And when an enterprise lacks the internal human capital to manage its ledger, it doesn’t just face an efficiency problem; it faces a durability crisis.

The Automation Paradox

This question betrays a fundamental misunderstanding of leverage. AI is an excellent tool for computation, but it is a catastrophic failure at accountability. Strip away the “grunt work” of the accounting cycle. This removes some friction, but it does not remove the need for a pilot. In fact, the more automated a system becomes, the more devastating a single error becomes.

The Logic of the Stakeholder

The “Human Element” is often dismissed as a sentimental variable. In a boardroom, it is a practical one. For instance:

• A computer has no skin in the game. It cannot be fired, it cannot be sued, and it feels no reputational sting.

• Every stakeholder, from the IRS to lead creditors, require a throat to choke. They demand a human signature that represents a commitment of professional ego and livelihood.

• If a process can be done by anyone with a $20/month subscription, that process ceases to be a competitive advantage. It becomes a baseline. The value is no longer in the “doing.” The value is in the “guaranteeing.”

The Durable Path

The firms that will dominate the next decade are those that view AI as a way to scale responsibility, not just output. This inherently gives boring old professional service firms an opportunity to change perception, and perhaps will create a whole new category/industry.

There is a lot of capital chasing professional service firms to “integrate” them in some kind of marketable roll up. It seems pretty clear the strategy is to own the change management, but what is being discounted at scale is the difficulty of deploying change. The fundamental habit of trading hours for dollars and learning the art of trading Certainty for Margin.

The most obvious variable to me is accountability.

I’m currently navigating this paradox. When demand exceeds capacity, you face a binary choice with three distinct mechanics.

The Friction of Excellence

In a boutique advisory or service firm, you cannot “scale” quality through a software update. You scale through people (even in the AI age). To maintain a high standard, you must hire ahead of the demand curve.

This creates a structural “cash gap.” You are deploying capital to acquire high-level talent today to service revenue that may not stabilize for 90 to 180 days. For a fast growing firm, this creates a permanent state of working capital depletion.

The Three Levers of Expansion

When your ambition outstrips your cash flow, you have exactly three variables to manipulate and each comes at a cost:

1. Controlled Stasis (The “No” Lever): You decline new engagements and grow only at the rate of retained earnings.

   1. The Cost: High opportunity cost and potential loss of market share.

   2. The Benefit: Zero financial risk and total preservation of quality.

2. Equity Injection: Bringing in outside partners to fund the talent acquisition.

   1. The Cost: The most expensive form of capital. You are trading forever cash flow for temporary liquidity.

   2. The Benefit: Improves the balance sheet without adding the pressure of debt service.

3. Debt Financing: Using credit facilities to bridge the gap between hiring and billing.

   1. The Cost: Introduces interest expense and a fixed obligation that persists even if demand dips.

   2. The Benefit: Non-dilutive. It allows founders and operating partners to retain 100% of the upside.

The Inversion Principle: What if you don’t grow?

If we invert the problem, the goal isn’t “maximum growth”, but durable growth. Taking on debt to fund a “talent bench” is a rational move if, and only if, the LTV (Long Term Value) of the client base significantly exceeds the cost of the capital and the risk of a market correction.

The financial truth of the service business is simple. You are a capital allocator who happens to sell expertise. If you cannot fund your growth through your own margins, you must pick a path.

Part I: Alpine Mar

2025 is Alpine Mar’s 5th year in business, and this year was by far it’s biggest and most active year. Here are the quick highlights:

• Our team grew from 9 in 2024 to just over 40 today.

• Part of Alpine Mar’s growth in 2025 came by way of an acquistion in Q1 that added 7 new members to the firm and an added service line, Assurance Services. Read more about it here.

• We’ve expanded our international team and added a physical office location in the Philippines to continue to attract exceptional local talent. Our Philippines team today is comprised of 16 members. Read more about it here.

• We launched a new business under the Alpine Mar umbrella expanding into IT services, which was a natural segue to support many of our existing clients in new ways. Read more about it here.

• Our AI adoption and workflow automation efforts were exceptional this year. As we close the year our Client Accounting Services (CAS) practice deployed AI agents into QuickBooks Online for a few small, select group of clients. The results have been impressive, and the team will be looking to expand these capababilities in 2026.

While 2025 has been an exceptional year of growth for the firm, it did not come without challenges. Integrating an acquired firm, launching a new business, and implementing new processes through rapid technological shifts is no easy feat. It was achievable as a result of one primary attribute that sets our firm apart. THE PEOPLE. This is something I take a lot of pride in, and has in large part informed our hiring processes. To date, our new hires are a product of our internal network. Whether we’re hiring here in the US, or in the Philippines, our first course of action is to look through the network of existing team members to identify other talented individuals in our industry.

The result of this has lead to quality, high pedigree, and high character individuals that make up Alpine Mar. What we’ve accomplished in such a short period of time would not have been possible without the exceptional individuals that make up our team.

Part II: AI Exploration

Alpine Mar has been defined as The Modern Day Accounting Firm, and for good reason. Like many other industries the AI buzzword is humming. We are not afraid of change, on the contrary, we welcome it. We’re leaning into the AI revolution. As a result, we embarked on an AI project toward the end of 2024. Our core focus at that time was:

1. How should AI be deployed in our business?

2. What are the biggest risks and concerns with AI in our business?

The first question prompted a wealth of responses that were obvious, but the second question was one that required us to be much more thoughtful, and careful with AI deployment. At Alpine Mar we work with a wide range of ultra high net-worth individuals and families, and small solo run businesses. We work with, and have access to very sensitive non-public information. Privacy and security is one of our single highest priority focuses at the firm. Therefore, if we are going to deploy AI in our business, data security was priority number 1.

This lead to the hiring of an emerging tech engineer that spent over a decade in the AI space with two exceptional companies, Oracle and Boeing. We were immediatley impressed with a platform he had built that allowed the local, on device deployment of AI, rather than having a need to rely on a cloud based infrastructure that we didn’t own, and could potentially expose data. We spent a few months testing the platform, and while it was impressive, we ultimately found that in order to deploy the solution at scale within the firm, we would need a lot more hardware. The short conclusion is this: computing hardware has not caught up to the needs for the local deployment of AI at scale. The exact reason massive amounts of capital are going into data centers.

Part III: AI Start up

Fortunately, later in 2025, many security challenges are being solved, and new industry specific tools are being released by other companies we’ve begun to partner with. However, this isn’t the end of that AI development. Before scraping our project altogether, we asked for a lot of feedback in the emerging tech community. This lead to a conversation with an engineer working for one of the largest embedded processing chip makers, for products like Amazon Alexa and Google Home. He’s since become a part of the team.

While the product that had been created was not suitable to deploy at scale with the massive amounts of data we retain, it is suitable for embedded edge devices, such as what is currently thought of as a smart home device. Our society in general is becoming more privacy concious, while “big tech” is becoming more invasive. The platform that has been developed focuses on this exact problem, while also delivering greater capabilities than what the world has come to know from devices like Amazon Alexa.

The team is in the process of deploying and testing the software on NVIDIA dev kits so that we can start understanding how far we can push an LLM’s size and capability on an embedded device. Turning on your TV, your lights, and other applicances is just the begninning, and the cool part, you don’t need internet to make it happen. All AI compute is happening locally, on the device. No threat of big tech listening in to steal your data, and even better, no subscription necessary. This doesn’t mean the device won’t connect to the internet. It just means you’re more in control of when you do and what you share.

There’s much more to come on this as the team continues to build. Hopefully a new household name will emerge from this project, but if it doesn’t, it won’t be a failure. I will still be walking away with a ton of new knowledge.

Part IV: 2026 Outlook & Closing

As I look forward to 2026, our main focus point at Alpine Mar is not growth. It is to coninue providing an exceptional, high level of service to our exisiting clients. Continued growth will be a by-product of our exceptional service and our ability to partner with, and attract and develop new talent. To that end, we are in the process of developing training resources within the firm. It is not enough to simply attract great talent, but it is our responsiblity to develop and promote great individuals. This is a phase within Alpine Mar that I’m very excited about.

Aside from my core responsibliity of managing Alpine Mar, I hope 2026 will bring some more time for me to do some more writing, and to have more conversations with some of the exceptional people I have in my network on Roads & Riches. Two things that I genuinely enjoy.

In closing, I also want to share that I think writing and having in person conversations is more important now than ever. The reason being is that AI is an incredible tool, and one that I beleive, if not careful, can rob us of thinking critically and being creative. Even if it can do those things better than us as humans, there is a level of fulfillment that comes with thinking critically, solving problems, and being creative. Be intentional about doing more human things in the world of AI - I beleive it is important.

I wish you all a wonderful holiday season, and a great closing to the 2025 year!

Pablo

(not written by AI)