Tianyu Hou, CFO, sold 15,000 Class A ordinary shares of Sea Limited(SE +1.58%) on July 17, 2026, according to a recent SEC Form 4 filing.
Transaction summary
Metric
Value
Transaction value
$1.5 million
Shares sold
15,000
Post-transaction shares (directly held)
2,428,015
Post-transaction value
$252.63 million
Transaction value based on SEC Form 4 weighted average sale price ($103.26); post-transaction value based on July 17, 2026 market close ($104.05).
Key questions
What was the mechanism for this transaction? The sale was conducted through a Rule 10b5-1 trading plan adopted on March 19, 2026, which allows corporate insiders to sell a predetermined number of shares at set times to manage personal portfolios.
What is the scale of the insider’s remaining equity? Following the sale, Tianyu Hou continues to hold 2,428,015 shares directly, representing a total equity position valued at $252.63 million based on the July 17, 2026 market close.
How does the transaction price compare to recent performance? The shares were sold at $103.26 per share, occurring as the stock’s one-year return reached -38% as of the July 17, 2026 transaction date.
Which entities were involved in the ownership change? The 15,000 shares sold were held through a BVI entity controlled by Tianyu Hou, while all remaining reported shares are held in the insider’s direct name.
Company Overview
Metric
Value
Share Price (as of market close 2026-07-17)
$104.05
Market Capitalization
$62.5 billion
Revenue (TTM)
$25.2 billion
Net Income (TTM)
$1.6 billion
Company Snapshot
Sea Limited operates a diversified digital platform ecosystem spanning digital entertainment through its Garena brand, e-commerce operations, and digital financial services across Southeast Asia, Latin America, and other international markets.
The company generates revenue through multiple channels including in-game monetization and eSports events within its digital entertainment segment, transaction fees and marketplace commissions from e-commerce operations, and financial services offerings including digital payments and lending solutions.
Sea Limited serves a broad consumer base across emerging markets in Southeast Asia and Latin America, targeting mobile and PC gamers, online shoppers, and consumers seeking digital financial services in regions with high growth potential and expanding digital adoption.
Sea Limited is a leading digital platform operator with significant scale, commanding a $62.5 billion market capitalization and generating $25.2 billion in TTM revenue across its integrated ecosystem. The company’s competitive advantage derives from its diversified business model that leverages network effects across gaming, commerce, and fintech segments, combined with deep market penetration in high-growth emerging markets where digital adoption continues to accelerate. Sea Limited has established itself as a critical infrastructure provider in digital commerce and entertainment across Southeast Asia and Latin America.
What this transaction means for investors
Amid a slew of trading plan-driven Sea Limited stock sales this past week, it’s important to note here that Hou is the finance chief, the executive with the clearest view of the books, which makes what he kept more telling than what he sold. His direct position of over 2.4 million shares, worth roughly $253 million, is virtually untouched: He sold just six-tenths of a percent of it.
Meanwhile, the numbers he oversees have been strong, even if the stock has been intensely volatile amid broader uncertainty around e-commerce competition, with first-quarter revenue climbing 47% to $7.1 billion and adjusted EBITDA passing $1 billion. In the firm’s earnings report, CEO Forrest Li noted that the firm is starting to see improved unit economics thanks to strategic investments that have also boosted topline growth. Whether these metrics meaningfully improve and continue will likely determine how Sea’s stock moves forward in the coming quarters.
Southwest Award Sale: Flights from 7,000 Points, Hawaii & International from 10,000
Southwest Airlines has launched a new Rapid Rewards award sale featuring one-way domestic nonstop flights starting at just 7,000 points. The sale also includes Hawaii and international flights starting at 10,000 Rapid Rewards points on select routes.
The promotion is valid on eligible award bookings made by July 20, 2026, at 11:59 PM PT. Most travel within the continental U.S. is valid from August 18 through November 18, 2026, while travel to Hawaii, Puerto Rico, the U.S. Virgin Islands, and international destinations has separate eligible travel periods and blackout dates.
Keep in mind that Southwest award pricing is dynamic and tied to the cash fare, so prices can fluctuate based on demand. Award bookings also require payment of applicable government taxes and fees, which start at $5.60 one-way.
You can see the promotion page here.
Important Terms
Book by July 20, 2026, at 11:59 PM PT.
Domestic nonstop award flights start at 7,000 Rapid Rewards points.
Hawaii and international award flights start at 10,000 Rapid Rewards points.
Most continental U.S. travel is valid August 18 – November 18, 2026.
Separate travel windows and blackout dates apply to Hawaii, Puerto Rico, the U.S. Virgin Islands, and international destinations.
Taxes and government fees start at $5.60 one-way.
Valid on select nonstop flights and subject to availability.
Guru’s Wrap-up
This is a solid opportunity to get more value for your Rapid Rewards points, particularly if you’re planning fall travel. Starting at 7,000 points for domestic flights and 10,000 points for Hawaii and international destinations, there are plenty of deals to be found if your travel dates are flexible.
This is also a good time to check any award flights that you have already booked to see whether the price has dropped.
A duplex. A fourplex. Maybe a single-family rental in a good school district. It feels manageable, the numbers make sense, and honestly it’s kind of exciting to finally put some of that W2 income to work.
And for a while, it works really well.
Then at some point, something shifts. Capital gets tied up. Finding the next deal takes longer. Management starts taking more time than you expected. And the math, the whole reason you got into this, stops moving the needle fast enough to feel worth it.
This is the ceiling almost every physician investor hits at some point. And I want to be clear about something: hitting it isn’t a sign that you did anything wrong. It’s actually a sign that you’ve learned enough to do something bigger.
Disclaimer: This article is for informational and educational purposes only and does not constitute financial, legal, or investment advice. Any investment involves risk, and you should consult your financial advisor, attorney, or CPA before making any investment decisions. Past performance is not indicative of future results. The author and associated entities disclaim any liability for loss incurred as a result of the use of this material or its content.
Thousands of physicians have joined Passive Real Estate Academy with no finance background, no investment experience, and no idea what a syndication is.
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Why Small Multifamily Has a Natural Ceiling
There’s nothing wrong with duplexes and fourplexes. They’re genuinely a great starting point. But they have structural limits that become obvious once you’ve been at it for a few years.
The first is a capital problem. Every property ties up a down payment. Once you’ve bought 10 or 12 units across several small properties, you often find yourself out of liquid capital with no clear path to the next deal. You’re not doing anything wrong. You’ve just hit the math ceiling of the strategy.
The second is a management problem. Small multifamily scales linearly. Each new property adds complexity: a new lease, new maintenance issues, new tenant relationships. You add rooftops, but you don’t really add systems. At a certain point you’re just adding to your own workload.
The third is a valuation problem. Small multifamily is priced like residential real estate. The value of what you own is driven by comparable sales in the neighborhood, not by how much income your property generates. That distinction matters a lot when you’re trying to actually build equity over time.
The physicians who break through this ceiling don’t do it by buying more duplexes. They change strategies entirely.
What Changes When You Go Commercial
Moving from 1 to 4 units into 5 units and above puts you in commercial real estate. The rules are different here, and some of those differences genuinely favor physicians.
The biggest shift is in how properties are valued and financed.
In commercial real estate, value is driven by income. Specifically by Net Operating Income, or NOI, which is just the property’s revenue minus its operating expenses. What this means practically is that you have real control over what your asset is worth. Improve the property, raise rents to market rate, reduce vacancy, and you’ve created equity. You’re not just waiting for the neighborhood to appreciate.
Financing works differently too. Commercial loans are underwritten primarily on the property’s income, not on your personal W2. For physicians with complex income situations, practice ownership, 1099 income, multiple income streams, this can actually work in your favor. The property carries more of the argument.
The honest trade-off is that commercial lending is relationship-based. There’s no standard product you fill out online. Lenders want to understand your track record, your plan, and how well you know your market. Building those relationships before you need them is one of the most valuable things you can do as an investor.
Three Ways Physicians Actually Make the Jump
The good news is that the transition doesn’t require starting over. There are three bridge strategies worth understanding.
1031 Exchanges
A 1031 exchange lets you sell a property and defer capital gains taxes by rolling the proceeds into a like-kind investment. For physicians who’ve held small multifamily for a few years and built up some equity, this is often the cleanest path to trading up. You keep your capital working instead of handing a chunk of it to the IRS.
The timing requirements are real: 45 days to identify a replacement property and 180 days to close. You need a qualified intermediary in place before you sell. But if you know your next market, this is one of the most tax-efficient tools available.
TIC Partnerships (Tenants in Common)
A TIC structure lets two or more investors co-own a property with clearly defined ownership percentages. It’s flexible, and it solves a problem a lot of physician investors face: you’ve found a good deal but don’t have enough liquid capital for the full down payment.
With the right partner, you can access deals that neither of you could reach alone. One partner brings capital. The other brings deal flow, market expertise, or operational capacity. The important thing is getting the partnership agreement right before closing. Expectations that aren’t written down tend to become problems later.
Physician-Specific Lending Products
Some banks and credit unions that specialize in physician lending offer business loan products that can be used for bridge capital or down payments on commercial deals. These are unsecured or practice-based loans that treat physician income differently than conventional lenders do.
The rates are typically higher than conventional financing, so this isn’t the right tool for every situation. But for physicians who’ve found a strong deal and need a capital bridge to get to the closing table, knowing these products exist is genuinely useful.
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What Actually Gets You There
Here’s something I think gets missed in a lot of conversations about scaling. Most people assume the jump to commercial is primarily a capital problem. Get enough money together and the deals follow.
In practice, two things matter more than the capital itself.
The first is knowing your market. Not generally knowing it. Knowing it well enough that your underwriting isn’t really a guess. What do rents actually support in this submarket right now? What are vacancy trends doing? What are buyers paying per door? Investors who scale consistently tend to have put in the repetitions on a specific market until the numbers feel second nature.
Conservative underwriting is where that knowledge gets applied. The investors who build durable portfolios almost always stress-test their assumptions: higher vacancy than the seller projects, lower rent growth, higher expense ratios. The goal is to structure a deal so that even in a difficult scenario, you’re still okay. A lot of your protection comes from how you buy, not from what happens after.
The second is lender relationships. This one surprises people. The terms available to a borrower with a real track record and an established relationship are genuinely different from what’s available to someone calling a lender for the first time. Showing up before you have a specific deal in hand, introducing yourself, understanding what a lender looks for, that’s not just networking. It’s infrastructure.
Knowing When You’re Ready
There’s no perfect moment to make this move. But there are some concrete signals worth paying attention to.
You’ve operated a few small multifamily properties long enough to know what the day-to-day actually looks like, not in theory but in practice.
You know a specific market well enough to underwrite a deal without leaning on the seller’s numbers.
You have at least one relationship with a commercial lender or broker who knows you’re a serious investor.
You have a clear picture of what you can fund on your own versus what a partnership or exchange could unlock.
If those things are in place, the move to commercial real estate is closer than it probably feels. The ceiling most investors hit in small multifamily is real, but it’s not the end of the road. For a lot of physicians, it’s just where the next chapter starts.
If you want to hear what this path looks like in practice, I recently sat down with Dr. Larry Daugherty, a radiation oncologist who scaled from his first fourplex to over 200 doors in Alaska. You can listen to that conversation here.
Were these helpful in any way? Make sure to sign up for the newsletter and join the Passive Income Docs Facebook Group for more physician-tailored content.
Peter Kim, MD is the founder of Passive Income MD, the creator of Passive Real Estate Academy, and offers weekly education through his Monday podcast, the Passive Income MD Podcast. Join our community at the Passive Income Doc Facebook Group.
Disclaimer: I am not a CPA, attorney, or financial advisor. The information in this post is for educational purposes only and should not be construed as tax, legal, or financial advice. Please consult a qualified professional about your specific situation before making any decisions.
Every time you enter a short prompt into your enterprise AI tool, behind that pulsing indicator you see on the screen, a flurry of invisible mechanisms and processes goes to work in the infrastructure. As the tool attaches the enterprise policies, session history, retrieved documents, and all the other contextual data it needs to generate a useful and reliable output, the dozen words you’ve typed systematically become a 40,000-token workload.
Now consider that thousands of users and agents may be hitting the system at once, each prompt reaching into a corporate knowledge base that, at the world’s largest companies, can run to 100 petabytes (PB). Serving from that archive generates a second active store, the key-value (KV) cache, that scales not with how much data you have but with how many users are querying it at the same time.
The expensive computation over those tokens becomes a cache worth saving and reusing to prevent redundancies and inefficiencies that bottleneck output. But the tool can only do that if the technical infrastructure has somewhere to keep that cache. And many enterprises don’t consider the need for this storage when they’re building AI infrastructure—until they run out of room.
To ensure enterprise AI tools can scale, the foundations designed to generate AI outputs must have the capability and the capacity to store the calculations of the complex operations that go into creating them.
And traditional options fall short at this scale: Fast but capacity-limited dynamic random access memory (DRAM) is too expensive to hold this data, and hard disk drives (HDDs) are too slow to serve it. Processing enterprise AI at the fleet level depends on high-capacity solid state drives (SSDs), which deliver the capacity to hold it and the speed to serve it—with the energy efficiency and footprint that make returns on AI investment achievable.
The Impact of AI Inference
As enterprises increasingly apply AI to their growth strategy, much of their focus remains on training larger and more capable models and investing in powerful graphics processing units (GPUs). But the bigger challenge now is inference: the process of serving AI responses accurately, reliably, and quickly at scale.
In modern AI systems, every prompt creates a bundle consisting of policy instructions, session history, retrieved documents, tool outputs, and other contextual components. This whole bundle is fed into an AI system where the expensive GPUs make computations. These computations—the KV cache—become reusable assets so the system doesn’t have to recalculate them over and over again. The KV cache represents a “state” within the AI system, and as AI deployments mature, managing that state becomes critical to performance.
The storage challenge only compounds as enterprises lean on retrieval-augmented generation (RAG), agentic workflows, and long-context reasoning over internal knowledge bases. Each of these increases the volume of information the system must store and access at once. And because much of that information has to be retrieved before the AI can respond, storage speed, not just capacity, shapes how fast the system feels to the people using it: the lag before a user sees a first response, known as time to first token (TTFT).
Although organization leaders often assume more GPU capacity powers faster AI, in reality, GPUs and other accelerators frequently sit idly while AI systems retrieve documents, load context, restore cached computations, or wait on data movement and storage bottlenecks.
The math scales quickly. A single long-context request can require 312 gigabytes of KV cache. Multiply that across eight concurrent users and the requirement jumps to 2.5 terabytes (TB). Add agentic workflows and the figure balloons to 10 TB—all of it needing to be stored, accessed, and managed with low latency.
A workload that may have initially appeared to be a manageable per-session memory requirement becomes a massive challenge when multiple users interact with AI simultaneously. Those saved calculations become one of the largest consumers of infrastructure resources.
That’s the “hidden storage tax”: issues that only become obvious when AI systems are put into production at scale. Even a task that appeared workable in pilots becomes unsustainable in practice as the number of users or AI sessions running simultaneously increases exponentially, known as concurrency. The result: slower responses, unforeseen bottlenecks, underused infrastructure, and higher operating costs.
Why Storage Is Critical
Historically, organizations have treated storage as a passive repository for their data—a holding place for data at rest. That approach worked when they were using storage primarily for backup systems, archives, and databases. But in AI environments, SSD storage is an active part of applications, critical to responsiveness, scalability, user experience, and cost efficiency. Enterprises that continue to use traditional benchmark metrics despite this shift are risking AI investments that can’t scale and failure of AI pilots.
These shifts are still emerging in inference, but the underlying principle is already visible wherever AI runs at scale: Storage architecture, not just compute, decides whether the system delivers.
PEAK:AIO, a software-defined storage provider, works with medical institutions using AI to analyze magnetic resonance imaging (MRI) scans to identify signs of cancer. These institutions generate enormous volumes of imaging data, but many lack the infrastructure they need to store, access, and analyze this data efficiently. PEAK:AIO offers its customers high-capacity SSDs so they can store and process large data sets within their own systems and networks.
For its containerized modular data centers, DUG Technology, a provider of high-performance computing and AI infrastructure solutions, uses SSDs to allow its customers to run AI systems in locations where the ability to deploy storage infrastructure is limited, such as industrial sites, energy facilities, and other remote areas.
A Day-Zero AI Decision
The right storage architecture can improve responsiveness, infrastructure efficiency, and scalability for long-context inference, RAG, and agentic AI workflows.
As enterprises expand AI initiatives, it’s becoming increasingly critical for AI architects—as well as leaders in procurement and finance, platform engineers, and other decision makers—to build technical foundations with sufficient high-capacity SSD storage to handle their operations and prevent bottlenecks today and in the years ahead.
And that means storage needs to be a part of the design conversation from the start—so their enterprises can avoid needing to invest in retrofitting their infrastructure later.
Read Solidigm’s “Anatomy of a Prompt” article and technical paper to learn why long-context AI, RAG, and agentic workflows are turning prompt design into an infrastructure decision—and how enterprises can qualify storage before latency, cost, and utilization problems show up in production.
✅ LinkedIn (Parth Sir):
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00:04 Understanding Excel settings and functions for Financial Modeling
02:17 Learn how to optimize Excel for financial modeling
07:07 Learn about financial modeling in Excel and how to optimize your calculations and save time
09:33 Automate data table updates and use automatic calculation for efficient financial modeling.
14:44 Learn how to use the analysis tool pack in Excel for regression analysis.
18:03 Learn how to set up the analysis tool pack in Excel.
22:30 Learn how to format cells and columns in Excel
25:32 Learn Financial Modelling step-by-step
30:23 Formatting numbers in Financial Modelling
32:25 Understanding the conventions of color coding in financial modeling.
37:56 Learn how to audit and format cells in a financial model
39:55 Learn to avoid hardcoding numbers in financial modelling
45:51 Learn to group and organize data in financial modelling
48:44 Highlight the gross profit and add a border
52:33 Understanding the process of changing and checking formulas in financial modelling.
54:58 Understanding and implementing partial anchoring in revenue calculation.
1:01:29 Understanding and implementing financial modelling techniques
1:04:03 Immediate results from 5% with 100% impact.
1:09:48 Learn about custom formatting and applying it to numbers.
1:12:55 Hard coding and absolute anchoring are important in financial modelling.
1:17:40 The start date for this year is 15th August.
1:20:25 Learn about casting analysis and how to link cells in financial modelling
1:25:57 Min function is used to find the smallest number in a sequence
1:28:48 Learn how to express the condition ‘if less than’ in financial modeling
1:35:36 Learn Financial Modelling – Step by Step – Session 2
It’s a very light week of data with only weekly initial jobless claims on Thursday and flash U.S. services PMI on Friday.
The dearth of reporting means the focus will be on the ongoing conflict in the Middle East, which has ratcheted up lately.
The U.S. just completed a ninth consecutive night of strikes against Iran in a bid to weaken their attack capabilities on ships navigating the Strait of Hormuz.
Despite that, oil prices have eased from their highs, though they have ticked up again recently.
As such, any mortgage rate movement this week will likely be tied to geopolitics.
Limited Economic Data Means the War Will Drive Mortgage Rates This Week
As noted, there’s not much on the economic calendar this week. We get jobless claims every week so that’s a given.
And there’s virtually nothing else until Friday, when we get the flash U.S. services PMI, which provides a snapshot of the economy and whether it’s expanding or contracting.
It’s known as an important report, but pales in comparison to things like CPI, PCE (the Fed’s preferred inflation gauge), and the monthly jobs report.
So that means we’ll be looking at geopolitical developments to determine the direction of mortgage rates this week.
They had a bit of a wild ride last week, with the 30-year fixed climbing to its 2026-high of 6.75% on Monday, before easing thanks to a series of cool inflation reports.
Mortgage rates ran the risk of hitting new-52 week highs, but fortunately both CPI and PPI came in below consensus.
That “saved” mortgage rates, though it only allowed them to ease back down to around 6.625% instead of perhaps climbing to 6.875% and beyond.
Can We Continue to Avoid 7% Mortgage Rates?
One thing I’ve been keeping a close eye on is a return to 7% mortgage rates.
Thus far, despite the surge in oil prices and the threat of even more escalations in the Middle East, mortgage rates have stayed below 7%.
The 30-year fixed has gotten close, but it seems to have a lid that has kept it from reaching those psychologically-challenging heights.
But there are reports that Houthi militants in Yemen have “declared a maritime embargo” against Saudi Arabia, which is apparently effective immediately.
The Saudis have been moving their oil to an export terminal on the Red Sea to bypass the Strait of Hormuz.
Assuming this makes a real impact, it could choke off more oil supplies and lead to another increase in prices, putting more pressure on inflation again.
Bonds (and mortgage rates) suffer when inflation rises, so this will be the key story to watch this week and beyond.
As I said, mortgage rates have done a good job avoiding bigger losses in spite of what’s going on there.
Though on the other side of the coin, they are still up sizably since the Iranian conflict got underway around the end of February.
The 30-year fixed was priced just below 6% at that time, and today is closer to 6.625% to 6.75%.
That’s roughly 75 basis points higher, meaning you could argue a lot of it is baked in already, which is helping us steer clear of 7%.
However, if this conflict continues and/or worsens, it’s possible we go higher. And we aren’t too far from 7% in the grand scheme.
What’s keeping us from that seems to be a belief that negotiations could still be reached to end the conflict.
At which point we ideally get back on track to pre-war levels when rates were closer to 6% and below.
Read on: Try out my mortgage rate calculator that compares rates/payments by eighths of a percent.
Before creating this site, I worked as an account executive for a wholesale mortgage lender in Los Angeles. My hands-on experience in the early 2000s inspired me to begin writing about mortgages 20 years ago to help prospective (and existing) home buyers better navigate the home loan process. Follow me on X for hot takes.
IRS data shows the student loan tax bomb has historically been tiny: the Joint Committee on Taxation estimated it collected only about $6 million per year.
The tax bomb was paused from 2020 through 2025, but now student loan debt cancelled under income-driven repayment is taxable again.
The student loan tax bomb is back. Since the American Rescue Plan’s tax exemption for forgiven student debt expired on December 31, 2025, borrowers who reach forgiveness under income-driven repayment (IDR) plans once again face a potential federal income tax bill on the canceled balance.
But here’s the question almost nobody asks: how much did the tax bomb actually cost borrowers when it was the law before? And what can borrowers actually expect to pay moving forward?
The historical answer, buried in IRS data and congressional budget estimates, is surprisingly low. The harder question (how much it will cost going forward) is one nobody can honestly answer yet.
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What The IRS Data Actually Shows
Canceled debt is generally taxable income, reported to borrowers and the IRS on Form 1099-C. The IRS tracks how much canceled-debt income taxpayers actually report on their returns, and the numbers have been shrinking for years.
In tax year 2019, 518,174 returns reported $5.46 billion in cancellation-of-debt income (all debt types combined, not just student loans). That was down from 770,756 returns and $10 billion in 2013, when the housing crisis was still working through the system. Applying ordinary tax rates of 12% to 22% to the 2019 figure, Americans paid roughly $650 million to $1.2 billion in federal tax on all canceled debt that year, or about $1,300 to $2,300 per affected return.
Just as notable is who never paid. An estimated 5.5 million Forms 1099-C were filed for tax year 2012, yet only about 770,000 returns reported canceled-debt income that year.
The vast majority of canceled debt is not taxable, largely because of the insolvency exclusion. Insolvency is what happens if your debts exceed your assets when the debt is canceled, some or all of the forgiven amount isn’t taxed.
The Student Loan Slice Was Even Smaller
Within those canceled-debt totals, student loans were a a tiny fraction and the government’s own estimates prove it.
Before 2018, federal student loans discharged due to death or total and permanent disability were taxable. When Congress moved to eliminate the tax through the Stop Taxing Death and Disability Act, the Congressional Budget Office and Joint Committee on Taxation estimated the change would reduce federal revenue by just $6 million in the first year and $69 million over a decade.
In other words, the Treasury was collecting single-digit millions per year from the most active version of the tax bomb because most affected borrowers were insolvent, low-income, or both.
Prior to 2020, idea of the student loan IDR tax bomb (a giant bill after 20 or 25 years of payments) was almost entirely theoretical. However, a big reason was failed loan forgiveness policies.
An NPR investigation found that as of 2021, 4.4 million borrowers had been in repayment for at least 20 years, but only 32 had ever received IDR forgiveness. You can’t pay a tax on forgiveness that never arrives.
Why The Future Is Different – And Unknown
History says the tax bomb barely detonated. But that many be changing in the future.
The American Rescue Plan’s exclusion has expired, making IDR forgiveness taxable again at the federal level. Public Service Loan Forgiveness remains tax-free, and the One Big Beautiful Bill Act permanently excluded death and disability discharges.
What’s left exposed is exactly the population that used to be theoretical: long-term IDR borrowers.
Payment-count adjustments moved millions of borrowers years closer to forgiveness, the SAVE plan’s collapse is pushing borrowers into IBR and the new Repayment Assistance Plan, and RAP’s 30-year forgiveness currently has no tax exclusion at all.
The IRS Taxpayer Advocate has already flagged the change, and NASFAA notes that borrowers whose forgiveness was delayed by processing backlogs may avoid 1099-Cs for now.
Nobody knows how big the post-2026-era tax bomb will be, and it’s worth being honest about why.
We don’t know how many borrowers will actually reach forgiveness each year, how many will qualify for the insolvency exclusion, whether Congress will extend tax-free treatment again before large cohorts hit their milestones, or how aggressively states will tax forgiveness on their own.
The historical record (tiny collections, mass avoidance through insolvency, and repeated congressional intervention) suggests the aggregate impact may again be smaller than feared. But the number of borrowers approaching forgiveness is orders of magnitude larger than anything before.
What This Means For Student Loan Borrowers
The practical risk isn’t the national total, it’s whether you’re personally impacted. A borrower with $80,000 forgiven in the 22% bracket faces a potential $17,600 federal bill, before state taxes. Our student loan tax bomb calculator can estimate your exposure.
Three factors decide how real it is for your household.
1. Timing: forgiveness dated in 2025 was tax-free, while the same forgiveness dated in 2026 may not be.
2. Solvency: if your debts exceed your assets at discharge, Form 982 and the insolvency exclusion can wipe out some or all of the tax, and long-term IDR borrowers with negatively amortized balances are disproportionately likely to qualify.
3. Program: Which forgiveness path you’re on matters more than ever, since PSLF stays tax-free while standard IDR forgiveness does not.
If you think you’re going to face a tax bomb issue, it’s best to speak with a tax professional at least a year in advance to see if there’s any planning you can do. Not all tax professionals may be versed in insolvency either – so make sure you talk to a few and know your options.
The Chase Sapphire Dallas Fort Worth International Airport (DFW) Lounge is now open.
Located post-security in Terminal D by Gate D25
More than 18,000 square feet across levels
In person photos here
Access rules here
More lounge options are always a good thing even if you don’t have access as it helps with capacity at other lounges. This looks nice and it’s certainly big.
Spain just won the FIFA World Cup following a grueling match against Argentina. And it was all thanks to Ferran Torres scoring in the 106th minute, capping off a dramatic extra-time thriller. Now, he’s being hailed as the hero of Spain‘s triumph—but just four years ago, he found himself in the biggest career rut of his life.
In 2022, the Spanish forward was grappling with a mental health crisis; the then-21-year-old had hit rock bottom after his €55 million ($62.8 million) move from Manchester City to La Liga club Barcelona. Torres was struggling to handle the pressure that came with his talent’s high price tag, just as he was recovering from a preseason leg injury and crushing Europa League loss to Eintracht Frankfurt.
“I found myself in a bottomless pit, and I could not see a way out,” Torres told reporters in 2023. “It had never happened to me before. That was the moment when I decided to work with a psychologist.
“I lost my confidence. Everything was affecting me,” he continued. “Seeing [a psychologist] will become increasingly normalised in football. There are weeks when I don’t go and others when I go three times. We don’t always talk about football, we also talk about my private life.”
Torres credits therapy as “one of the best experiences” and making him stronger as a person. And his story can resonate with many; behind the trophies and multimillion-dollar contracts, many sports stars are fighting battles that most fans never see. As many as 51% of elite athletes struggle with mental health problems at some point in their lives, according to a 2020 study. Most commonly, they’re up against struggles like depression and anxiety, and may put off seeking help due to social stigma.
But the 26-year-old’s multimillion-dollar sports career and World Cup title is proof that prioritizing mental health doesn’t derail greatness—it can help unlock it.
Now Torres is a World Cup champion earning millions every year
Torres’ rise has been a story of early ambition turned into global success, with the young forward quickly becoming one of soccer’s most recognizable stars.
Born in the small coastal town of Foios, Spain (right outside of Valencia), Torres was destined for the world stage from an early age. At just six years old, he joined Valencia CF’s academy and made his professional debut at 17. After gaining a reputation as one of Spain’s top emerging talents, he signed with Manchester City in 2020, winning both the Premier League and League Cup.
Barcelona then paid millions to the English team to bring him back to Spain in 2022, and his high-profile transfer was followed by injuries, intense pressure, and a crisis of confidence.
Torres eventually rediscovered his spark thanks to his therapist, becoming a key contributor for both Barcelona and Spain. He went on to win multiple domestic trophies, including La Liga, the Copa del Rey, and the Spanish Super Cup. And what is sure to be one of the highlights of his soccer career, Torres scored the winning goal for his country in the 2026 FIFA World Cup.
The Gen Z footballer has also been raking in million-dollar contracts since his twenties. In 2020, Torres signed a five-year, $12 million contract transferring from Valencia to Manchester City. He spent several years on the English team before then making his return to Spain in 2022, signing a five-year deal with Barcelona for an initial €55 million ($62.8 million), with another €10 million ($11.4 million) in add-ons.
Estimates put Torres’ current base salary between $6.3 million to $10 million per year—or around $120,700 to $192,000 every week. It’s also reported that his sizable paycheck comes with at least another €3 million ($3.4 million) in bonuses every year; and off the pitch, he’s landed brand deals and partnerships with Under Armour.
Opinions expressed by Entrepreneur contributors are their own.
Key Takeaways
Google Search isn’t all people are using these days. Artificial intelligence tools such as ChatGPT, Perplexity, Claude, Gemini and others have become popular search engines — and the ways we optimize our online presence for AI are different from Google.While AI search continues to evolve,
AI search continues to evolve, and if you don’t want to get left behind, there are four signals your business needs to get right to stay at the top of the search results page.
Recently, a client came to me with a problem that turned out to be anything but small.
On paper, their business was thriving. Their clientele was loyal. The offer was polished, and the team was exceptional at what they did. Yet when people searched online for their business, particularly inside the newer AI tools, they were nowhere to be found.
This client did not need another generic marketing checklist. They needed a real strategy to be seen. They needed to appear where people actually search today, not where they searched a decade ago.
Today, people are not only typing business names into Google. They are asking ChatGPT. They are turning to Gemini. They are consulting Perplexity. They rely on AI to decide who to trust, where to go and which expert deserves their business.
So if your company is built only for old-school search, you are playing yesterday’s game.
I watch this every single day across all of my businesses. AI search keeps evolving and I have no intention of being left behind. More importantly, I refuse to let my clients be left behind either.
Search isn’t just ranking anymore — it’s your reputation
For a long time, search felt fairly predictable.
You chose smart keywords. You placed them across your site. You pursued a few backlinks. But that version of search is no longer the full picture.
The bigger question now is not simply, “Where do I rank?” A better question is, “Do new ways people search the internet trust my business enough to recommend me?”
That is an entirely different game. Now your business has to be more than findable. It has to be worth recommending.
I think of it this way: Old search was about landing on the list. Modern AI search is about earning the introduction.
Different search engines want different things
One of the most common missteps I see owners make is assuming every search platform behaves the same way. They do not. Google, ChatGPT, Gemini, Perplexity, Claude and the rest each have their own way of finding, reading and sharing information. They overlap, but they are far from identical.
Some lean heavily on indexed web content. Some look for trusted sources and citations. Some study reviews and reputation closely. Some want clear, structured details so they understand exactly what you offer.
Picture each platform as a different customer. One wants credentials. One wants social proof. One wants receipts. One wants to hear what your clients think. One simply wants everything explained plainly. Your task is to make certain they all leave satisfied.
I build genuine proof across the web: clear messaging, strong content, accurate business details, press signals, reviews and a consistent story. When that foundation is right, your visibility begins to travel.
The 4 signals I build for every business
Your customers look for four signals: trust, authority, relevance and reputation. Get those four things right, and you give every engine more reasons to notice you and recommend you. If they are weak, even a beautiful website can struggle.
1. Trust
Trust is the starting line. Before anything recommends you, it needs to feel certain you are real and consistent. Your name, address, phone, website and profiles should match everywhere. You would be amazed how many businesses have mismatched versions of themselves drifting around. To clients, that looks careless. To search tools, it looks risky.
2. Authority
Authority is when credible sources vouch for you. Press, interviews, podcasts, articles, partnerships and recognition all help. You can praise yourself all day, but when a respected source says it, that carries real weight. I would rather earn one strong mention in the right place than 50 weak ones nobody trusts.
3. Relevance
Relevance is clarity. Engines need to understand what you do, who you serve and where you operate. Vague phrases like “solutions for modern businesses” sound impressive but say nothing. Be clear in your messaging.
4. Reputation
Reputation is what people say when you are not in the room. Reviews, testimonials and social proof shape how you are perceived. You cannot fake it for long. You earn it by doing exceptional work, inviting delighted clients to share positive reviews about your business.
Why this is so important
Here is the part people do not love to hear: AI search is not a fix-it-once-and-forget-it affair. There is no finish line. Platforms change. Results change. Competitors improve. Reviews arrive. Signals shift.
So I treat visibility as an ongoing part of every business I touch. AI search evolves daily and I refuse to wake up six months from now to discover a competitor became the answer to their question while I ignored the question. I check. I test. I ask AI tools what they recommend. I watch who appears and why. It is like glancing at your dashboard. You do not stare at it all day, but you want to know the moment the warning light flips on.
What this means for you
If you own a business, the truth is simple: Your clients already use AI search, ready or not. They ask for recommendations and weigh their options. If the tools they trust never mention you, you may never get the chance to compete.
Start by seeing what is actually happening. Ask Google, ChatGPT, Gemini and Perplexity about your industry and local market. Notice who appears. Then strengthen your foundation. Refine your information. Build real reviews. Create clear content. Earn credible mentions.
The winners in this new era will not be the loudest. They will be the clearest, the most trusted and the easiest to recommend. I am not chasing rankings like it is 2012. I am building trust across the entire web.
Key Takeaways
Google Search isn’t all people are using these days. Artificial intelligence tools such as ChatGPT, Perplexity, Claude, Gemini and others have become popular search engines — and the ways we optimize our online presence for AI are different from Google.While AI search continues to evolve,
AI search continues to evolve, and if you don’t want to get left behind, there are four signals your business needs to get right to stay at the top of the search results page.
Recently, a client came to me with a problem that turned out to be anything but small.
On paper, their business was thriving. Their clientele was loyal. The offer was polished, and the team was exceptional at what they did. Yet when people searched online for their business, particularly inside the newer AI tools, they were nowhere to be found.
This client did not need another generic marketing checklist. They needed a real strategy to be seen. They needed to appear where people actually search today, not where they searched a decade ago.
