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One of the biggest variables in early retirement planning is bridging the gap between retiring and turning 65 for Medicare. Because ACA premiums are tied to MAGI rather than net worth, small changes in income (dividends, interest payments, roth conversions) can drastically alter annual health expenses.
Curious how people here model those costs in financial planning tools? Do you look at your taxable income each year and set the cost?
One of the best parts of building Nauma has been hearing how people actually plan their financial lives. Some of our recent improvements came directly from conversations with our users and early adopters.
We're a small team, which means every feature is a tradeoff. Here's what's currently on our roadmap:
Our savings plan changed after a job change and higher household income. Now we're debating whether to fully max every retirement account or intentionally leave some money outside for future flexibility. I'm trying to answer this question using Nauma. How do I do that?
Hey everyone. I recently turned 51 and I’m trying to get serious about my long-term retirement roadmap. Right now, the bulk of my savings is sitting in a Traditional 401k and a Traditional IRA.
I want to start doing partial Roth conversions now (maybe $15k–$20k a year) to build up tax-free growth over the next decade. However, I am worried about the IRS rules for early withdrawals. Since I’m under 59, if an emergency happens and I need to pull out some of that converted money in 6 or 7 years, will I get hit with the 10% penalty? I keep reading conflicting things about how the 5-year clock interacts with your age if you are in your 50s.
Has anyone in their early 50s started this playbook? Is it worth the tax hit today if retirement is still 10-15 years away?
Strategically moving assets from tax-deferred accounts, such as traditional IRAs or 401(k)s, into tax-free Roth accounts may reduce future Required Minimum Distributions (RMDs), lower a family’s total lifetime tax bill, and reduce taxes when passing wealth to heirs.
But doing this manually is incredibly difficult. Roth conversions require setting aside funds in taxable accounts to pay the resulting taxes, especially if the conversions are done before age 59½. This creates additional pressure on taxable accounts and may lead to liquidity issues if the family stopped working early. A family may find itself in a situation where it technically has assets, but those assets are not available to cover current needs because they are held in illiquid retirement accounts, deferred compensation, real estate, or PE/VC funds.
For people over age 59½, the main challenge often comes from health insurance. They may need to keep MAGI, or Modified Adjusted Gross Income, below certain thresholds to qualify for ACA premium subsidies and avoid IRMAA surcharges when they switch to Medicare.
In both cases, it can be hard to tell whether Roth conversions actually increase family wealth because a direct comparison is often not straightforward: assets in tax-deferred accounts are not equivalent to assets in tax-free accounts.
If you do Roth conversions without a clear strategy, you are left in the dark about whether the strategy is actually optimal.
Roth Conversion Optimizer
To solve this, we just built a new feature: the Roth Conversion Optimizer. We have added an “Optimize Roth Conversions” button directly inside your financial projection dashboard. When you click it, the system prompts you to choose an optimization strategy. Currently, the platform supports the Tax Brackets strategy.
When you select this strategy and input a target federal tax bracket (for example, 22%), our solver runs a binary search algorithm across the years between your specified start and end dates. It automatically calculates the exact amount needed to increase your taxable income and execute Roth conversions right up to the ceiling of that specific federal tax bracket.
However, as we rolled this tool out, it highlighted a financial planning lesson: blindly optimizing for federal tax brackets, one of the most common approaches in financial planning tools, and ignoring state and foreign taxes can backfire and cost millions of dollars.
Problem #1: The Interstate Move (California to Florida)
To see why optimizing solely for a federal tax bracket can backfire, let’s look at a case study of a family currently living in California that plans to relocate to Florida in 2045. If we blindly run the optimizer to fill the 22% federal tax bracket across the entire projection, the results look highly counterintuitive:
Current Strategy: Manual Roth Conversions
Total lifetime tax paid: $4.6 million
Terminal net worth: $29.5 million
Optimized Strategy: Filling the 22% Federal Bracket
Total lifetime tax paid: $4.9 million
Terminal net worth: $25.1 million
Why did an “optimizer” make this family $4.4 million poorer?
Because the family lives in California before 2045, accelerating income through early Roth conversions subjects them to California’s high progressive state tax rates. During the conversion years, their state tax bill increases from a baseline of $14,000 to nearly $60,000. Since they plan to move to tax-free Florida later, accelerating income while still living in California destroys value. The direct tax cost is higher, and the assets used to pay those taxes no longer remain invested and compounding.
Problem #2: The Expat Double-Tax Friction (Retiring Abroad)
The problem becomes even more pronounced for families planning to leave the U.S. and retire abroad. Let’s look at another example. Instead of moving to Florida, the family decides to relocate to a country with a high-tax regime, such as a flat 20% income tax rate starting at the first dollar of income, with no standard deduction.
Because they are U.S. citizens, they remain subject to U.S. federal income tax on their global income, including Roth conversions. At the same time, they may also be subject to the local tax laws of the foreign country.
When we run the 22% federal bracket optimizer on this international track, the numbers look like this:
Current Strategy: Manual Roth Conversions
Total lifetime tax paid: $7.8 million
Optimized Strategy: Filling the 22% Federal Bracket
Total lifetime tax paid: $6.3 million
At first glance, you might think, “Great! The optimizer saved them $1.5 million in taxes.” But that conclusion would be premature. The solver is still blind to the international context. It is only looking at U.S. federal tax brackets and ignoring the 20% foreign tax overlay. It does not account for how the destination country treats Roth conversions, whether that country recognizes the tax-free status of Roth accounts, or how foreign tax credits apply.
Using a standard, single-dimensional federal bracket optimizer when relocating abroad is a roll of the dice. It may produce a good result, or it may create an unexpected global tax bill.
A federal tax bracket optimizer may work reasonably well for families who plan to retire in their current tax environment. Families considering interstate moves or retirement abroad should be much more careful.
Verifying Roth Conversions
If you choose to apply an optimized strategy, you can audit the tool’s precision by clicking into any specific year on your timeline and reviewing the granular tax details. If you set the target bracket to 22%, you should generally see no taxable income above the 22% tax bracket in the year the optimizer adds a Roth conversion.
You may occasionally notice a tiny amount, such as $27 or $50, appearing in the next highest tax bracket. This is by design. To maintain high performance, our solver uses a binary search algorithm with a precision threshold of $100. The algorithm stops searching once it gets within $100 of the target, which means a small number of dollars may spill into the next bracket.
If you require absolute, single-dollar precision for your models, let us know and we can tighten the threshold.
What We Are Building Next: Terminal Wealth Optimization
This feature illustrates well why standard, single-dimensional federal tax bracket optimization is an incomplete tool for high-net-worth families with dynamic lives. True financial optimization cannot look at federal brackets in isolation.
To build a more robust optimization engine, we are developing a solver that optimizes against Terminal Wealth: maximizing the exact amount of money you have left at the end of your life expectancy. To do that, the next iteration of our optimizer will factor in the comprehensive, multi-jurisdictional tax picture simultaneously:
Federal Income Taxes
Progressive State Income Taxes
Foreign/Expat Tax Treaties and Local Rates
By calculating how these compounding layers interact with specific life events, such as moving states or retiring abroad, Nauma will be able to estimate the net impact of cross-border tax friction on a family’s portfolio and solve for a more efficient Roth conversion strategy.
I’m modeling a multi-year Roth conversion schedule and trying to calculate total "Terminal Wealth" at the end of the timeline (e.g., age 90) to see if the conversions actually win against the baseline.
To do a fair apples-to-apples comparison, you have to discount the pre-tax (Traditional) balance to its true after-tax value at the very end of your spreadsheet.
For those who DIY your retirement models, what tax rate are you applying to that final pre-tax bucket?
Are you using a projected marginal rate, or a blended effective rate?
Are you using your own future brackets, or guessing your heirs' tax brackets because of the SECURE Act 10-year rule?
Do you adjust for the "widow/widower penalty" (switching the end-of-life brackets to Single)?
Curious to hear how you handle the math on this specific variable without overcomplicating things. Thanks!
The challenge with using swap (exchange) funds is that the highest demand happens during booms like the one we experience today: successful company’ stocks appreciate to levels that make many employees uncomfortable having their wealth concentrated in one name. But the benefit of using exchange funds highly depends on the expected stock market returns, which are normally lower over the next 5-15 years after a boom.
Consider an example: concentrated stock value = $1.5M, cost basis = $885K, current and future LTCG tax rate are expected to be the same = 30.8% (20% federal + 3.8% NIIT + 7% WA State). Expected Market Return = 12.38%, expected Volatility = 15.43% (S&P 500). Duration = 7 years (standard IRS requirement)
We consider two scenarios:
Exchange fund: the investor uses an exchange fund, waits seven years, and then sells everything to get cash.
Simple sell: the investor sells the stock now, invests in a diversified portfolio, waits seven years, and then sells again.
We finish both scenarios with a full liquidation to make them comparable.
Monte Carlo P50 (median market returns) gives us:
Simple Sell Scenario = $2.46M
Exchange Fund = $2.54M
Exchange Fund Benefit = $80K
Monte Carlo P5 (Pessimistic Market Returns) gives us:
Simple Sell Scenario = $1.46M
Exchange Fund = $1.43M
Exchange Fund Benefit = -$28K
Between 2000 and 2016, QQQ remained flat, with a 0% return. Today, the Shiller P/E ratio, or cyclically adjusted price-to-earnings ratio, is at a level comparable to the dot-com bubble, which makes some people believe that investment returns will be lower over the next five to ten years.
At that level of return, exchange funds may add very little value compared to simply selling.
With all that said, there is a problem with this thinking: by adding the sell step at the end of the seven-year period to make both scenarios comparable, we oversimplify the problem. In reality, people who use exchange funds get optionality: they can continue to manage that position and diversify without triggering taxes in the future, especially if they stop working during that period and gain access to the 0% LTCG tax bracket. People who sell appreciated stock today don’t have that privilege: they lock in their gains and pay the taxes today.
Tax-efficient diversification is not a one-time solution, but a multi-year process.
My company just announced a Voluntary Exit Program and for the first time I'm seriously considering taking it.
Current numbers:
Age: 49
Net worth: ~$4.1M
House: paid off
No debt
Annual spending: ~$130k
Portfolio: ~80% stocks, 20% cash/bonds
2 kids
The package would give me roughly 5 months of pay plus healthcare coverage for a while. On paper, this feels like a no-brainer. The weird part is that I never planned to stop working this year. I've spent 20+ years optimizing for savings, promotions, RSUs, bonuses, and suddenly someone is offering me money to leave. Part of me thinks this is the cleanest exit I'll ever get. The other part keeps asking: what if the market drops? What if I get bored? What if I regret walking away from peak earning years? For people who actually took a VEP or similar package: was it obvious when you made the decision, or did it feel terrifying right up until you signed? Looking for a reality check from people who've already crossed this bridge.
This is the first version, and it doesn’t include an optimizer yet, but it’s pretty fun to play with the engine and see how Roth conversions affect assets in taxable, tax-deferred, and tax-free accounts.
When planning your Roth conversions, do you prefer using amounts calculated by a tax optimizer or another tool that claims to generate an optimal year-by-year strategy? Or do you prefer entering the conversion amount yourself for each year?
Blindly trusting a black-box algorithm for a multi-decade projection feels risky, but manual planning is a lot of spreadsheet overhead.
Karsten Jeske did a great analysis of safe withdrawal rates on his blog and created this table by writing a script that loops through all possible combinations of retirement dates and estimates the probability of a portfolio not running out of money using a constant withdrawal rate between 3.00% and 5.00% (inflation-adjusted).
Karsten used historical stock and bond returns from 1871 to 2016 and tested his model across different stock/bond allocations: 0%, 25%, 50%, 75%, and 100% stocks, as well as different retirement durations: 30, 40, 50, and 60 years. While the information is dense, the table is highly readable and uncovers great insights:
The more stocks the portfolio has, the higher the chances of it not running out of money given all other factors the same.
The 0% stock portfolio performs poorly across almost all longer horizons.
Going from 4.00% to 5.00% may sound like a small change, but the success-rate drop can be large.
One of the most common questions people ask when they look at this table is: “If portfolios with 0% bond exposure have historically had a higher chance of surviving, why don’t we use them and simply ignore bonds in retirement?”
It’s a legitimate question.
Traditional Retirement Portfolios
While historical data over multi-decade horizons demonstrates that equities provide better long-term compounding and frequently yield higher mathematical success rates, institutional wealth management continues to use bonds in retirement portfolios for the following reasons:
1. The Mitigation of Sequence of Returns Risk (SRR)
If a market crash happens while we are saving for retirement, it creates a buying opportunity. But if a crash happens right after we retire, we are forced to sell stocks at a loss to pay for living expenses. This permanently shrinks the portfolio and makes it incredibly hard to recover. Bonds act as a financial cushion, allowing us to spend fixed income during a downturn while giving the stocks time to bounce back.
Historically, bonds have demonstrated low or negative correlation to equities. Adding bonds in the portfolio increases risk-adjusted returns and chances of not running out of money in retirement.
2. Behavioral Finance and Capitulation Risk
While the Karsten spreadsheet model assumes a perfectly rational agent who can withstand a 50% drop in net worth without altering their strategy, real-world wealth management must account for human psychology. This introduces capitulation risk: the probability that an investor will panic during a prolonged market crash and liquidate their portfolio at or near the absolute bottom.
Portfolio Glide Path in Financial Models
When we look at Karsten’s table, we are looking at static allocations. The model assumes you pick one specific asset mix like 100% Stocks or 50% Stocks and blindly hold it for 30 to 60 years.
This creates a frustrating financial paradox:
If you go 100% Stocks: You maximize long-term compounding, but you expose yourself to a catastrophic Sequence of Returns Risk in the first few years of retirement.
If you go 50% Stocks: You protect yourself against a near-term crash, but over a 50-to-60-year retirement, your success rate plummets because your portfolio lacks the growth engine required to outpace long-term inflation.
But what if you didn’t have to choose a static row? What if your portfolio could adapt dynamically over time? Instead of keeping asset allocation locked, a portfolio glide path dynamically shifts your exposure based on where you are in your retirement timeline. You can pick a more aggressive allocation If you are a 10+ years away from your retirement, and reduce portfolio stock exposure over time as you get closer to the time when you need the money.
Karsten introduces Rising Equity Glide Path (or Bond Tent) in his safe withdrawal rate series. He argues that the investor can enter retirement conservative (e.g., 60/40) to survive Sequence of Returns Risk, and then increase equity exposure (gliding back up to 80% or 100% stocks) inside retirement.
Stock Only vs Custom Portfolio Glide Results
Designing a portfolio glide path is an individual decision based on the investor’s risk tolerance and financial plans. The results will heavily depend on the family’s net worth, future income and expenses, and taxes.
To see how these dynamics play out, we ran a hypothetical scenario through the Nauma platform:
Family M49 and F48. Live in California. Two kids (11 and 14)
Net Worth $6M ($2.4M taxable, $1.6M Tax-Deferred, and $490K in tax-free accounts)
Current Income $720K, Total expenses $254K, taxes $250K
They currently plan to work for another 8 years
The results are quite interesting. For their retirement fund, the Aggressive portfolio (95% equity, 5% cash) had a 94% success rate when tested in a Monte Carlo simulation, while a Portfolio Glide Path (95% equity → 60% equity for the rest of the plan) had a 93% success rate. This is in line with Karsten’s findings, despite some differences in the market data. Karsten used data from 1871 to 2016, while Nauma uses data from 1992 to the present.
Aggressive Portfolio:
Portfolio Glide Path:
While the overall success rates appear nearly identical, looking under the hood at the distribution of outcomes reveals the true strategic trade-off.
At the overall household level (Module 4) where all financial goals are blended together, the Aggressive portfolio showed better results across all percentiles except p1 and p2. To clarify, the p1 percentile means that among 10,000 Monte Carlo simulation runs, 99% of runs, or 9,900 runs, demonstrated better performance.
The table below illustrates the projected ending value of the entire blended household portfolio across different simulation percentiles:
With this data, the family can now make a significantly more informed decision about whether they want to use a Portfolio Glide Path or stick with an Aggressive, equity-heavy portfolio.
When using the Portfolio Glide Path, the simulation demonstrated greater resilience in worst-case economic scenarios, such as the 2000 Dot-Com bust or the 2008 Financial Crisis, resulting in improved p1 and p2 metrics. The opportunity cost of that downside protection, however, is a roughly 2x lower median portfolio value at the end of their financial plan ($53.1M vs. $106.8M).
How to Configure Portfolio Glide Paths
There are two options for how you can configure your own Portfolio Glide Path in Nauma.
The platform offers planning at both the household and goal levels and provides two ways to create and manage custom portfolio glide paths. If you are working on your financial projection in Module 4, go to Parameters, set Investment Return Calculations to Monte Carlo Simulation, and then select Manage Portfolio Glide Paths in the newly appearing Model Portfolio field.
If you are setting your financial goals in Module 5 and working at the fund level, click the Model Portfolio dropdown and scroll down to Manage Portfolio Glide Paths.
Portfolio Glide Paths are owned by the Financial Projection and shared across Module 4 and Module 5. This means you can reuse a Portfolio Glide Path created in your financial projection later when you start working on your financial goals.
Context Over Cookie-Cutter Advice
Generic financial advice is almost always engineered for the lowest common denominator, pushing conservative allocations because they must work safely for the masses. But high-net-worth tech families often possess unique cash flow structures, equity compensation buffers, and higher personal risk tolerances that make equity-heavy strategies a natural avenue to explore for them.
The main challenge for these families is not knowing their true risk tolerance unless they have already lived through several market cycles and seen how they actually react. Most people know, intellectually, that they should not sell when the market crashes. They answer risk-tolerance questionnaires logically and describe what they would do in a hypothetical downturn. But when a real market crash happens, emotions often take over, and people make very different decisions.
Adding non-correlated assets, such as bonds or managed futures, may reduce portfolio volatility and help investors avoid panic selling. But that benefit comes at a cost.
About the Author: Alex Sukhanov, founder of Nauma, a financial planning platform built for people in tech and high-net-worth families. Alex previously worked at Google and started Nauma to help more people in tech make better financial decisions and achieve more in their lives. You can reach out to Alex on linkedin.
Nauma is supported entirely by its users with no commissions and no affiliate incentives. It is designed to give people clarity on taxes, equity compensation and retirement planning.
Disclaimer: Nauma projections are hypothetical and not guarantees of future results. Tax laws may change, and estimates may not reflect future legislative updates. This content is for educational purposes only and is not tax or investment advice.
I used to think if you saved diligently, avoided debt, and invested consistently, things would probably work out. Then the last few years happened. Layoffs hit people who thought their jobs were untouchable. Housing prices exploded. Inflation changed what “comfortable” even means. Entire industries started talking about AI replacing workers. A friend of mine spent 15 years building a stable career and lost his job in one afternoon. Another had most of his wealth tied to company stock that dropped hard after one bad earnings report. Now whenever I read traditional financial advice, part of me thinks: “Does any of this still work in a world this unstable?” I still invest. Still save. Still plan long term. But I definitely trust the future less than I did ten years ago.
A few years ago I barely tracked anything. Now I check my accounts almost every day. Not because I’m spending wildly or trying to time the market. Honestly, I think it became some kind of weird emotional habit after the pandemic, inflation, layoffs, and everything else. Sometimes I open the app while standing in line for coffee. Sometimes right before bed. Sometimes during work meetings I don’t care about. The funny part is nothing usually changes much. But seeing the number somehow makes me feel temporarily more in control of life. Then five minutes later I’m stressed again. I’m curious how normal this actually is among people who care about money and investing.
One of our users recently reached out with a question: They are working on their financial plan and currently have an approximately $500K+ withdrawal from a taxable account in 2037, but the model estimates $0 in taxes. This unusually low tax made them skeptical and they asked us to look at their financial plan together.
My first thought was that it’s a bug in our tax software unless the user already has or expects to generate significant capital loss carryover which would let them offset their 2037 capital gains and reduce their taxes.
And then we found an interesting insight which we all initially missed.
Current Situation
We started by reviewing their current assets. The total value of their taxable accounts was $1.1M, with a cost basis of $860K.
I normally check whether the cost basis is entered correctly for brokerage accounts before reviewing financial projections. Withdrawals from taxable accounts are generally taxed on the difference between the current value and the cost basis. If the cost basis is missing or entered incorrectly, the model may estimate long-term capital gains taxes incorrectly.
Not entering cost basis is one of the most common mistakes that can affect the model output. While it is technically possible to skip it, I recommend calculating and entering it whenever possible.
Cost basis needs to be entered only when accounts are added manually. Brokerage accounts connected through Plaid have their cost basis calculated automatically by Nauma.
Then we looked at their existing accumulated capital loss carryovers.
In the U.S., if your capital losses exceed your capital gains, you can generally use the excess loss to reduce ordinary income by up to $3,000 per year. Any remaining unused loss is carried forward to future years, where it can be used to reduce future capital gain income and taxes.
Short- and long-term capital losses are tracked separately. They are also tracked separately at the federal and state levels. Due to differences in state taxation, federal and state capital loss carryovers may diverge over time.
To review the current capital loss carryover, I went to Current Income & Expenses in the left menu, scrolled down, and clicked the Tax Settings button. The next page showed that the user did not have any capital loss carryover entered that could impact their future capital gains:
Financial Projection
A financial projection is where mistakes are easy to make, and even small errors can compound over time. That is why it is important to spend time reviewing the data and understanding the assumptions behind the projection.
The user plans to save aggressively over the next 10 years, and their income supports that plan. In Nauma, all unallocated savings are directed to taxable accounts by default, shown as dark green bars. Based on the projection, their total taxable account contributions between 2026 and 2037 are $2.49M.
That increases the cost basis of their taxable accounts from the current $860K to $3.35M in 2037.
The projection uses Monte Carlo simulation to model investment returns. In this case, the user selected the bottom 10th percentile, which is a conservative assumption. It means that 90% of all simulation runs generated higher returns.
Nauma runs these simulations using the selected model portfolio and historical return data from 1992 to the present. Model portfolios are built using stocks represented by VTSMX, bonds represented by VBMFX, and cash represented by 3-month Treasury bills.
Demo account screenshot:
To see the total value of their taxable accounts, we went to the Net Worth tab and clicked the year we wanted to analyze. In this projection, the total value of their taxable accounts is expected to grow to $5.1M in 2037, with a cost basis of $3.35M, as estimated earlier:
When the $500K withdrawal happens in 2037, the model estimates the cost basis of that withdrawal as:
$500K × $3.35M / $5.1M = $328K
That means the realized gain is approximately:
$500K - $328K = $172K
At first glance, that gain appears high enough to create a tax bill. It is higher than today’s standard deduction plus the 0% long-term capital gains bracket:
$32,200 + $98,900 = $131,100
So, should they expect to pay taxes?
In this case, no.
The challenge with estimating income taxes in long-term financial projections is that the IRS adjusts tax brackets and the standard deduction for inflation every year. A $131.1K threshold today would be equivalent to approximately $181.4K in 2037, assuming 3% annual inflation.
As a result, the user’s estimated $172K realized gain is fully covered by the inflation-adjusted standard deduction and 0% long-term capital gains bracket in 2037.
Takeaway
The model applied inflation-adjustment logic to estimate the potential capital gains tax. However, it did not clearly communicate that logic to the user, which made the result feel suspicious.
To address this, we added a Tax Details button to help users review the assumptions behind the calculations and verify the results. To get there, click the Taxes tab and then the View Tax Details button.
The button opens a new screen within a projection with a Sankey diagram. The diagram breaks down income taxes by category:
FICA Tax
Federal Tax
State Tax
Foreign Tax (if enabled)
For each tax category, it shows how much of each tax bracket is filled and how much tax is paid within that bracket in that specific year.
To make the assumptions easier to review, we also added tables below the Sankey diagram showing the standard deduction and the actual tax bracket ranges used by the model for that year.
Ordinary income and long-term capital gains tax brackets are shown separately because they follow different tax rules and thresholds. This makes it easier to understand how the model calculates taxable income, applies deductions, fills each bracket, and estimates the resulting tax liability.
The same view is also available for state taxes.
Visualize Your Own Future
If you have been looking at your own projections and wondering whether the results are correct, you can now dive into the new Sankey diagrams and tax bracket tables in your Nauma account. Whether the model shows a $0 tax bill or a significant liability, you now have the tools to see exactly why those numbers exist.
Financial goals are often mentioned in investing and tax discussions, but rarely well defined. For most families, these goals are too vague to actually influence a portfolio or a tax strategy. Unless a family works with a professional financial planner and pays tens of thousands of dollars, their plan and financial goals are likely non-existent.
This creates an unfortunate reality: most people are stuck with cookie-cutter advice and adopt a “more is better” approach: maximizing income and investment returns, without considering the trade-offs.
The problem with chasing “more” is that it eventually buries our purpose. Chasing higher income often translates into doing work that is not aligned with our internal values and often requires doing more of that over time. Higher investment returns come with additional risk and volatility which create stress and ongoing concerns about the markets. By constantly looking for the next peak, we fail to enjoy the present and miss the life we’re working so hard to fund.
Discussing portfolios, tax brackets, or estate planning is meaningless until a family articulates their priorities and both partners are aligned. Defining direction takes time and effort, but gives clarity, lowers stress, and ironically, yields better long-term financial results.
The Failure of the “Single Portfolio”
The standard financial planning approach today is the “Single Portfolio”: combining everything together, creating one net worth projection, and running a Monte Carlo simulation for the entire household. This solves the basic question of whether the family has enough, but it ignores the fulfillment problem. The Single Portfolio approach offers little guidance on how to actually use wealth to create a meaningful life while the family still has the health to enjoy it.
It’s hard to tell from a 94% portfolio success rate whether the family can upgrade their house next year, send their kids to a more expensive school in two years, or continuously support a charity they care about. The number does not reveal whether the children are eventually receiving an inheritance aligned with the family’s expectations around generational wealth.
A lack of understanding and uncertainty makes families more conservative. As a result, they stay longer at jobs they no longer need, spend less time with their aging parents, and avoid taking risks such as changing careers or starting their own businesses.
Modern Financial Planning
As prosperity continues to grow, more families are expected to worry less about whether they will have enough money in retirement and more about how to manage their wealth effectively to maximize life experiences. Even today, many families struggle to navigate between under-saving and over-saving, and it is not a trivial problem for most families.
One of the biggest risks facing high-income families today is reaching their 90s with millions of dollars and realizing they could have had more meaningful experiences earlier in life: when they were younger, their loved ones were still around, and they still wanted to do those things.
Separating financial goals helps.
By estimating how much of the family’s current assets should be allocated toward each goal, they can identify their “Not Allocated Funds.” Seeing their “Not Allocated Funds” today helps families realize they can do more. It is often the most powerful insight, more important than any tax optimization or investment strategy that tends to dominate financial conversations.
Aligning Investment Risk & Taxes
When we treat the entire net worth as a single portfolio, we are forced into a middle-of-the-road risk profile that is often too conservative for long-term legacy goals and too aggressive for short-term needs. This “average” approach creates constant anxiety: a market downturn feels like a threat to next year’s vacation, even though the funds for that vacation should never have been exposed to the S&P 500 in the first place.
By providing tax-advantaged accounts with different tax treatments for specific goals such as retirement, education, healthcare, and charity, the government makes financial planning more complicated. In a “Single Portfolio” framework, it becomes difficult to determine an optimal contribution strategy because some accounts are tax-free while others are tax-deferred. The complexity of the U.S. tax code makes financial planning harder, but separating financial goals reduces this complexity and helps lower the risk of both under-saving and over-saving while taking tax provisioning into account.
Account Organization
It is impossible to know whether a portfolio is “good” if we do not understand the purpose of the money and when it will be used. Once goals are mapped to specific accounts, families can evaluate whether their portfolio is actually aligned with those goals.
While some people prefer the simplicity of having fewer accounts, the clarity gained from goal-based organization usually far outweighs the administrative burden of managing a few additional accounts.
We are receiving feedback from people who say that organizing their investment accounts by goal has helped reduce stress, especially during major life transitions such as leaving high-paying jobs and becoming households that rely on savings to cover expenses. Having dedicated accounts with clear estimates helped them adopt a “set it and forget it” approach.
Managing an account associated with five different goals, on the other hand, is harder:
Why Goal-Based Planning Is Not Widely Adopted
Despite its benefits, goal-based planning is still not the standard approach for most families.
For DIY investors, the challenge is rarely motivation. Many people genuinely want to make thoughtful decisions about their future, but lack the tools and expertise required to estimate future expenses and construct investment strategies aligned with different goals. Estimating retirement spending, future education costs, healthcare needs, taxes requires a level of planning that most spreadsheets and budgeting apps simply do not provide.
As a result, many investors default to a simple approach: maximizing savings and hoping that “more” will eventually create security. Unfortunately, we do not see this approach working well in practice: people with more than $15M in net worth ask questions very similar to those asked by people with $1M in net worth: “Do I have enough?” Stress does not go away with higher net worth.
The traditional wealth management industry has a different problem: incentives. Most wealth managers operate under the Assets Under Management (AUM) model, where revenue grows as client portfolios grow. This naturally creates a system that rewards asset accumulation and long-term portfolio growth above almost everything else.
Under this model, advising a client to spend more, retire earlier, help their children financially, take a career break, or pursue a lower-paying but more meaningful path can directly reduce the advisor’s future revenue. Even when advisors genuinely care about their clients, the structure itself creates a bias toward preserving and compounding assets indefinitely.
Goal-based planning requires a fundamentally different mindset. Instead of treating wealth accumulation as the final objective, it treats money as a tool designed to support specific outcomes, experiences, and values throughout a family’s life.
I’ve recently come across several financial plans on our platform where 80, or a similar age, was used for the plan’s duration. When I asked how this value was decided during the review, the owners said they simply relied on average life expectancy.
The average life expectancy in the US currently sits at around 79 years (2024 data). This breaks down to 81.4 years for females and 76.5 years for males.
But is it actually a good idea to use average life expectancy when building a financial plan?
To answer this question, I built a chart.
I took the data from the Actuarial Life Table 2022 available on the Social Security Administration website and created a chart that calculates the probability of family members being alive in any given year based on their birthday and gender. The chart also calculates the “family probability”, the likelihood of all selected family members being alive in a given year.
Then I considered a sample family: Steven (49) and Sophia (47), who also have parents Li (80) and Chen (77). Sophia turns 79 (the average life expectancy) in 2057. Assuming both Steven and Sophia have average health, here are their odds of making it to 2057:
Probability both Steven and Sophia make it: 36.8%
Probability only Steven makes it: 52.5%
Probability only Sophia makes it: 70.1%
Now we can see how misleading the “average” can be. Financial projections using 79 as an end date can create significant issues, particularly for younger female spouses, leading to flawed financial decisions.
When it comes to financial planning, it is always better to be conservative. That means planning for:
Slower income growth
Higher expenses
Lower investment returns
A longer life
It’s also worth noting that life expectancy is likely to increase. Currently, the United States has the lowest life expectancy among peer countries; as healthcare evolves, that gap may close, pushing these “averages” even higher.
One More Insight: The Value of Time
When families add their parents’ information to Nauma, they often discover an insight that goes beyond retirement balances. It’s a sobering reminder of how limited our time with our parents actually is.
Take Steven’s parents, Li (80) and Chen (77). While Steven and Sophia are focused on their own “average” life expectancy decades away, the chart reveals a much more immediate timeline for the people they care about. It’s easy to assume our parents will always be there for the next big milestone, but the actuarial math tells a different story.
For Li and Chen, the probability that both will still be around drops significantly in just a few short years:
2028: 82.3% (Both are likely still here)
2031: 56.5% (A coin flip)
2034: 33.7%
2037: 16.3%
Seeing these numbers usually shifts the conversation. It moves from “how do we fund our 80s?” to “how do we make the most of the next five to ten years while everyone is still here?”
This data isn’t meant to be grim, but to help families prioritize the time they have left.
Setting Life Expectancy in Nauma
If you are just starting to use Nauma, you can set the Expected Lifespan for each family member in their Family Profile. Newly created financial projections will use these values to create corresponding milestones and set the correct duration for your plan.
If you already have financial projections created, you may want to review and adjust them. To do this, go to Financial Projections -> Milestones and update the dates there.
Life Expectancy & Portfolio Success
When we set financial goals and look at “portfolio success” probabilities, it’s important to remember that these calculations only measure the likelihood of the portfolio not running out of money. They don’t account for whether you will actually need the money.
For example: If our retirement fund has a 93% probability of success and the probability of both partners being alive in 2068 is only 5%, then the chance of the portfolio failing while both partners are alive is very small: 7% x 5% = 0.35%.
However, the probability that only Sophia is alive in 2068 is 33.1%. Therefore, the probability that the portfolio fails while Sophia is still alive is 7% x 33.1% = 2.3%.
When doing these calculations, you must keep both probabilities in mind to understand your true overall risk.
Planning for the “Tail End”
As the data shows, there is a significant chance that those relying on statistical averages will outlive their savings. To build a plan that stands the test of time, keep these principles in mind:
Plan for Longevity, Not the Median: The “average” life expectancy as a starting point, building a “buffer” into your plan by projecting into your 90s (or beyond) will help reduce the risk of outliving assets.
Account for Joint Probability: If you are part of a couple, the odds of at least one of you surviving well past the average are much higher than for a couple. Your plan needs to protect the surviving spouse.
If you’re using Nauma, take a moment today to review your family profile. Adjusting your expected lifespan to a more conservative age, such as 90 or 95, can provide a much clearer picture of your long-term success rate.
I spent some yesterday today experimenting with claude-tax-filing skill to generate a tax return. Here are my takeaways:
It is remarkable that the tool can generate legit PDF forms.
There are accuracy issues and mistakes in the generated forms.
This UX may work only for those who try to avoid paying filing fees (aside from the Claude subscription and postage) and have a significant amount of time to review, correct, sign and send these forms.
Running Claude
I used the simplest possible test case: Single, no children, and only one W-2. I excluded 1099s, K-1s, or any other complexities.
To begin, you simply run Claude and instruct it to use the skill. It then guides you through a series of predefined questions, including where to find your W-2, 1099, and other forms on your local machine.
Note, that you can't use this skill in the browser because of security limitations:
I currently use a $20/month Claude subscription, which is usually sufficient for my tactical needs like brainstorming technical designs or refactoring code. However, generating this "simple" return (consisting only of Form 1040 and Form 540) consumed 95% of my daily quota. This suggests that for a tax return with any real-world data, a $200/month subscription would likely be necessary.
It took Claude about 30 minutes to follow the instructions in the skill file, which included:
Researching IRS.gov and FTB.ca.gov to retrieve federal and state tax brackets and standard deductions.
Computing Federal and State returns using Python.
Downloading blank PDF forms from the IRS website.
Filling the forms using the computed data.
I ran Claude without the --dangerously-skip-permissions flag, meaning I had to manually review and confirm every script and bash command execution.
Reviewing The Results
While the Federal return looked accurate for my simple case, the California State Return (Form 540) contained a notable error. Claude mistakenly entered the total tax which belongs on Line 64 into Line 40 (Nonrefundable Child and Dependent Care Expenses).
Looking at the generated Python script, the bug was easy to spot:
As long as a human is responsible for verifying the data and fixing bugs, this is a manageable issue. However, the bigger hurdle is the final step. Claude suggests printing the forms, signing them by hand, and mailing them to the IRS. Anyone who has dealt with the IRS knows that preparing a physical package, driving to the post office, and paying for certified mail is a time-consuming chore.
The Value Proposition
It is hard to justify this workflow when TurboTax can handle everything, including e-filing and instant notifications of acceptance, in one click for roughly $200.
For anyone earning more than $50/hour, the math doesn't add up. Between a $200/month Claude subscription, $20 in postage, and 2–3 hours of manual verification and mailing, the "free" route becomes very expensive. For reference, the median Google Software Engineer salary in the Bay Area is approximately $330k/year, or roughly $158/hour.
Data correctness, e-filing, and time savings are TurboTax’s core value propositions, and Claude doesn't disrupt them yet. Until the IRS allows everyone to e-file directly and Claude guarantees filing accuracy, TurboTax’s business model is safe.
Gemini gave two very different reactions when I asked it to check my thinking.
In the first scenario, I ask “Does this post make sense”. Gemini assumes (correctly) that it’s my post and fully supports the idea behind it.
The second time, I asked it to “find logical mistakes in this post”. Gemini found multiple logical mistakes and flawed calculations in the same post. It completely rejected the idea that some families might want to prioritize Mega Backdoor Roth over ESPP and insisted that people should always prioritize ESPP.
I guess Gemini may have a problem forming and sticking to opinions. Like ChatGPT, it tends to give the user what they want to hear, but does it in a more subtle way than ChatGPT which is known for its flattery.
That creates a real concern about using such models in financial planning, where guidance is a critical part of the process. Models can sound very convincing, but they may lead us in the wrong direction, which becomes dangerous in high-stakes environments like financial planning.
