President Donald Trump’s financial accounts made nearly 40 times as many trades in one month as those belonging to Treasury Secretary Scott Bessent, a Wall Street veteran with decades of experience.
Trump earlier this week disclosed 1,156 transactions made by accounts in his name in July, including 440 purchases and 716 sales, according to a report filed with the Office of Government Ethics. In total, his transactions represented at least $79 million and at most $270 million in trades, according to a Fortune analysis of the report. The exact dollar amount associated with each trade was not disclosed.
That compares with Bessent, who disclosed just 29 transactions for all of 2025.
All of Bessent’s transactions were sales, according to an Office of Government Ethics report. Several of the transactions involved his interests in entities related to Key Square, the hedge fund he founded in 2015 and left to join the administration. Others were sales of individual stock in companies like Verizon and Archer-Daniels-Midland. A JPMorgan Chase stake owned by Bessent’s husband John Freeman was also inadvertently reported as a deposit account previously and was adjusted, according to the report.
Bessent agreed to divest assets that could conflict with his new role when he agreed to become Treasury secretary.
As for Trump’s transactions, a White House spokesperson previously told Fortune the president’s assets are held in a trust measured by his children. Meanwhile, the large number of transactions is due to third-party “computer-based model portfolios that automatically replicate recognized indexes, such as the Schwab 1000,” the spokesperson told Fortune.
The White House did not immediately respond to Fortune’s request for comment.
A federal conflict of interest law 18 U.S. Code 208 legally prevents most federal officials from acts affecting a personal financial interest, but this doesn’t apply to the president and vice president. Trump’s volume of trading has ramped up during his second term. A disclosure filed with the OGE showed the president’s accounts recorded more than 21,000 transactions during his first year back in office.
To be sure, it’s unusual for a president to maintain ownership of an actively traded portfolio of individual securities while in office. Since Congress passed the Ethics in Government Act of 1978, all modern presidents have either adopted a blind trust or limited their investments to non-conflicting assets like diversified mutual funds, said Walter Shaub, the former director of the Office of Government Ethics, in 2017 remarks.
Just months before resigning as director of the OGE during Trump’s first term, Shaub said in remarks at the Brookings Institution Trump’s plan to handle his financials while in office, “doesn’t meet the standards that the best of his nominees are meeting and that every president in the past four decades has met.”
The scale of transactions stemming from Trump’s accounts has also prompted criticism from politicians like Sen. Elizabeth Warren (D-Mass.) and Rep. Robert Garcia (D-Calif.), who in a letter to Trump said: “The sheer volume of this trading activity and the timing of a number of transactions, raise questions about whether you are using your knowledge of government activities, your official authority, or the vast megaphone provided by the Presidency to make investments or move markets to your personal benefit…”
Yet meanwhile, Trump has backed new restrictions on stock trading for members of Congress. The Trump administration in July said it “strongly supports” the Stop Insider Trading Act, that would prohibit members of Congress and their families from buying stock in companies while in office. The bill was opposed by some Democratic lawmakers because it includes a provision that would impose new ID requirements for voting in federal elections.
While the House passed the bill this summer, it is still being considered by the Senate. The bill’s restriction on trading would not apply to the president and vice president.
X Money Drops Premium Requirement, Offers Up to 6% APY
X Money has made an important change to its new financial account: an X Premium or Premium+ subscription is no longer required. That’s notable because the monthly or annual subscription cost previously ate into the value of the account. Doctor of Credit reported the change on September 23.
X Money offers up to 6% APY, although eligibility varies. X’s official site says Premium+ users qualify for 6%, while other users may qualify for the boosted rate by meeting the qualifying direct-deposit requirement. X Money is not itself a bank; funds are held at Cross River Bank and other FDIC-insured institutions, with X advertising up to $10 million in FDIC coverage through its cash sweep program, subject to applicable requirements.
New York Residents Get a $300 Bonus Instead
There’s an important difference for New York residents. X Money does not currently pay interest in New York. Instead, New York customers can earn a $300 bonus after receiving $3,000 in qualifying direct deposits.
X defines a qualifying deposit as an ACH direct deposit with a PPD SEC code or qualifying X Creator payouts from Original Content Rewards, Creator Revenue Sharing or Creator Subscriptions. See terms here.
Up to 3% Cash Back With X Card
The X Card also offers up to 3% cash back on eligible purchases. However, the exclusion list has recently expanded and now includes categories such as utilities, wholesale clubs, insurance premiums, colleges and universities, and jewelry stores, in addition to several previously excluded categories (Utilities, Wholesale Clubs, Jewelry Stores, Watches, Clocks, and Silverware Stores, Insurance Underwriting, Premiums Colleges, Universities).
There’s also reportedly a $25 signup bonus, although some users have received only $15.
Guru’s Wrap-up
Dropping the X Premium requirement makes X Money considerably more interesting. Up to 6% APY plus up to 3% back on debit card purchases is a good combination, although you’ll want to pay attention to the growing list of excluded purchases.
These rates might not last long, but it should still be worth signing up and take what you can.
Your customers usually describe your value better than you do. In this episode, John Jantsch sits down with Joanna Wiebe to talk about getting their words onto your website, into your emails, and in front of the prospects who look just like them.
Wiebe lays out a lean approach to voice of customer research that a small business can set up in an afternoon. She explains how to put your messages in the right order so prospects move from feeling a problem to choosing you. She also shares where AI belongs in the process and where you should keep your own hands on the keyboard.
This one is for small business owners, marketers, and consultants who want copy that sounds like their best customers wrote it.
About the Guest
Wiebe is the founder of Copyhackers, and many copywriters call her the original conversion copywriter. For more than 15 years, she has taught copywriters, marketers, and founders to write copy that sells, with clients ranging from early-stage startups to AWS and Calendly. Her newest book is The Copyselling System: Write to Sell with the Secret Formula for Maximizing Revenue.
Key Takeaways
Interview about 7 customers, and choose the ones you most want more of. If you only have 2 ideal customers, interview those 2 and skip the rest.
Add one survey question to every confirmation page in your business: “What was going on in your life that brought you to [action] today?” Use a long answer box and pipe responses into Slack or a spreadsheet so your team sees them.
Before rewriting anything, find the bottleneck in your growth. Write a 1-page solution design by hand that names the constraint and shows where copy does and doesn’t fit the fix.
Move prospects through the stages of awareness in order. Start with problems in their life or business, then category challenges, and only then your product.
Let AI sort voice of customer data from sales call notes and online conversations into a shared message matrix spreadsheet. Your team writes the emails, and 60 words is a good target.
Great Moments
[05:57] Jantsch points out that people who answer a post-signup survey are making a small commitment that makes them more engaged with the business.
[14:38] Jantsch describes how marketers have lost control of the customer journey over the last 5 years because the way buyers research and buy has changed so much.
[13:28] Wiebe explains why prospects can’t tell your AI feature from a competitor’s weaker one, and why your copy should blame the category instead of the buyer.
[16:20] Jantsch asks whether businesses now need pricing, full reviews, and every case study online to answer the 100-word prompts buyers type into AI tools.
[22:10] Wiebe describes the “brain dulled” feeling of reading an AI draft and deciding to scrap it and write the thing yourself.
Memorable Quotes
“All we’re doing with research is trying to learn how to clone our best customers. And the way to clone them is to know what’s going on in their head and throw it on the page so everybody else who’s like them sees it.” – Joanna Wiebe
“The Copyselling System is intentionally called copyselling, not copywriting. Stop thinking about it as writing, just stop. Now we’re copyselling.” – Joanna Wiebe
“This is a place where you can start training AI on your message matrix, knowing that it’s more about AI knowing what to say about you than it is about you saying that thing about you on your website anymore.” – Joanna Wiebe
“AI came to party and I think we should party. But that means it has to come through for us too. We don’t just blindly accept whatever it says.” – Joanna Wiebe
“Humans make mistakes in their writing. They do run-on sentences, they abbreviate things, they use slang. Good human writing sounds like human talking, and if you read some of the AI copy, you think, I would never speak like that.” – John Jantsch
Resources
AI copywriting, Content Marketing, conversion copywriting, Copyhackers, copyselling, Copywriting, customer interviews, customer research, email marketing, Joanna Wiebe, message matrix, Small Business Marketing, stages of awareness, voice of customer, website copy
Yields on the US’s longest-dated bonds climbed to the highest level in more than two decades, the latest milestone in a global selloff driven by inflation fears and concern about government debt burdens.
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A fresh jump in oil prices on Thursday lifted five- to 30-year Treasury yields to new multiyear highs, with the 30-year rising to levels just shy of 5.5%, the highest since 2004. Ten-year yields rose 10 basis points to 5.21%, the highest since 2007.
READ MORE: Freddie must join MBS buying to ease 7% rates: CHLA
“It’s the aftermath of an explosion,” said Bryce Doty, a bond fund manager at Sit Investment Associates. “People are trying to pick through the debris for clues — is this an overreaction or the beginning of another move upward in yields?”
The rise in oil prices and broad inflation gauges over the past six months led the Federal Reserve to raise interest rates last week for the first time since 2023, and expectations for additional increases over the coming year have picked up. Swaps now fully reflect three quarter-point hikes over the next year from the Fed, with significant hedging for a fourth.
Oil prices — a dominant driver of Treasury yields since the US attacked Iran in late February, causing a Middle East supply shock — climbed as much as 5% Thursday after Iran threatened to expand the war.
In the Treasury market, two-year yields have climbed over 150 basis points since the start of the US-Iran war, while those on the 30-year are up over 80 basis points.
Mounting borrowing costs are a threat to the Republican majorities in congress in the November midterm elections, as dissatisfaction over lofty mortgage rates and the cost of living rises. US President Donald Trump has called for US interest rates to be “1%, or less” and criticized what he called a “hostile” Fed board for the decision to raise rates.
The continued yield rise undercuts the Treasury’s efforts to bring down long-term borrowing costs: Treasury Secretary Scott Bessent expanded the government’s bond buyback program in mid-August in an effort to ease pressure.
On Thursday, the department accepted $4.08 billion of the $6 billion maximum it targeted in an operation for 20- to 30-year securities. Yields rose, signaling disappointment with the outcome. The Treasury also bought back less than it sought at its in first expanded buyback on Sept. 10.
“What surprised the market was that they didn’t go to the full $6 billion after how much we’ve had a selloff in the last few days,” said Brij Khurana, a portfolio manager at Wellington Management. “I thought the purpose of the buybacks was to deal with drastic or illiquid price movement, and you could kind of argue that yesterday was that day.”
READ MORE: ARM demand rises as buyers pivot from high fixed rates
To Khurana, it leads to the question: “If they’re not going to buy back the max amount after these conditions, when are they going to?”
US five-year yields topped 5% for the first time since 2007 Wednesday — the market’s worst day in months as measured by the Bloomberg Treasury Index’s 0.73% loss — while those on 10-year jumped the most since the Liberation Day tariff shock in April 2025.
Global Selloff
The selloff extended to other major global bond markets, with European yields also mostly on the rise, and those on Japan’s government debt hitting levels last seen in 1996 as the market reopened after a three-day break.
The average yield on government debt worldwide now stands within a whisker of 4%, the highest since 2007, Bloomberg’s Global Aggregate Treasuries index shows. It’s another reminder of the end of the low-yield era as markets contend with the inflationary impact of the war in Iran, a robust US economy and a torrent of bond sales from governments and tech companies.
“It’s rare you get a move like this in bonds,” said Dave Aspell, co-chief investment officer at Mount Lucas Management LP, who is short 10-year bonds in the UK, Germany, Canada, Japan and the US. “The Fed has hiked again, inflation is clearly not at target. The economy is doing okay and there’s a large amount of government spending.”
Strategists at JPMorgan Chase & Co. and KKR & Co. see scope for US yields to climb further as energy-driven inflation, heavy government borrowing and the risk of additional central-bank tightening continue to percolate.
A $44 billion seven-year note auction on Thursday, meanwhile, was awarded at 5.085% — the highest on record since the tenor was reintroduced in 2009 — luring demand that fell short of expectations.
Rising volatility is adding to the gloom, making investors more hesitant to step in even as higher yields make bonds more attractive. The ICE BofA MOVE Index, which measures US bond market swings, climbed Wednesday to the highest level since March.
“Most fixed income will like higher yields, but want them to be stable there,” said Hans Mikkelsen, a strategist at TD Securities. Investors are “afraid of catching a falling knife,” he said.
Unit 2 focuses on understanding the fundamental concepts and theoretical foundations of management[1][2]. This unit provides students with comprehensive knowledge about the **nature of management** and explores various management theories that have shaped modern business practices.
### **Key Topics Covered:**
**2.1 Nature of Management**
– Understanding management as an **Art, Science, and Profession**[2][3]
– Exploring the different perspectives and characteristics of management
**2.2 Concept and Thoughts of Management**
The unit covers three major management approaches[1][2]:
– **Classical Approach** – Traditional management theories
– **Scientific Management** – Taylor’s systematic approach to management
– **Neo-Classical Approach** – Modern evolution of management thought
**2.3 Principles of Management**
This section emphasizes[2][3]:
– **Need for Management Principles** and their significance
– **Taylor’s Scientific Management** principles and contributions
– **Fayol’s 14 Principles of Management** – comprehensive guidelines for effective management practice
### **Learning Objectives**
Students will develop understanding of:
– The fundamental **nature and concept of management**[1]
– Various **theoretical approaches** to management thinking
– **Principles that guide managerial decision-making** and behavior[4]
– How these principles can be applied in real business scenarios
### **Assessment Focus**
The unit carries **25 hours** of instruction time and **8 marks** in the final examination[3]. Students are expected to understand both theoretical concepts and their practical applications in modern business environments.
This unit serves as the foundation for understanding how management principles guide organizational effectiveness and efficiency in achieving business goals[1].
Sources
[1] [PDF] Unit 2 – Concept of Management – CBSE Academic
[2] [PDF] Business Administration (subject code – CBSE Academic
[3] [PDF] business administration (833) – CBSE Academic
[4] Principles of Management class 12 Notes Business Studies
[5] Principles of Management Class 12 Business Studies Notes – Vedantu
[6] CBSE Class 12 Business Studies Syllabus 2023-24
[7] Business Studies Class 12 Notes – Free PDF – Vedantu
[8] Class 12 Unit 2 Principles of Management | PDF – Scribd
[9] [PDF] PRINCIPLES OF MANAGEMENT CHAPTER – NCERT
[10] [PDF] 2 principles of management revision notes
[11] Access NCERT Solutions for Class 12 Business Studies Chapter 2
[12] GNG Business studies | Day 2 | Chapter 2 | Class 12 – YouTube
[13] Class 12 Chapter 2 Business Studies Revision Notes | PDF – Scribd
[14] Class 12 Business Studies Unit 2 Principles of Management …
[15] [PDF] CHAPTER 2: PRINCIPLES OF MANAGEMENT – CASE STUDIES
Days Inventory Outstanding, or DIO, measures how long a company typically holds inventory before it is sold. Trade credit can plausibly be treated as operating credit while it finances that period, plus a reasonable administrative buffer for invoicing, reconciliation, quality checks, and payment processing.
But once payment duration materially exceeds DIO plus that buffer, the operational rationale weakens. The payable has outlived the physical flow of goods. The retained cash is no longer tied to inventory conversion. It is general liquidity.
A practical benchmark therefore focuses on excess payable days: the extent to which days payable outstanding (DPO) exceeds DIO plus the buffer. Payment days beyond that threshold indicate that the buyer continues to retain cash after the goods have been converted into sales. The debt-like amount is therefore the financing associated with those excess days, calculated as excess payable days multiplied by average daily cost of goods sold.
This is not an anti-trade-credit rule. It is a rule designed to protect trade credit. It preserves operating classification for the part of payables that plausibly supports supply-chain activity and reclassifies only the excess portion that behaves like financing.
The example is straightforward. If a retailer turns inventory every 40 days but pays suppliers after 120 days, the first 40 days may support the operating cycle. A further buffer may be justified for administrative and commercial frictions. But the remaining extension is difficult to explain as ordinary trade credit. It is liquidity provided to the buyer after the inventory has already been converted into sales.
The test is intended as an analytical benchmark rather than a universal bright-line rule. Operating cycles vary across industries and firms, and factors such as seasonality, inventory mix, supplier terms, and legitimate administrative delays may justify longer payment periods. The purpose of the threshold is therefore not to establish that every payable beyond it is debt, but to identify the point at which the operating rationale warrants closer scrutiny.
Once payment terms extend beyond the operating cycle, what operational purpose still justifies treating the liability as trade credit?
Ten minutes with AI might be all it takes to make your next hard problem feel harder.
None of what follows is a mistake in the way a leaked password or a made-up citation is a mistake. Nobody gets fired over these. Nobody files an incident report.
They’re quiet, documented patterns in how using AI changes your behavior. And if you use AI every day, there’s a good chance you’ve never heard of them. It’s become part of the day for a lot of people, which is exactly why these patterns are worth knowing.
These are the AI habits to be aware of. Each one comes from research released in 2026, and none of them is a reason to stop using AI. But all three are worth a moment of real thought.
Here’s what they are.
Disclaimer: While these are general suggestions, it’s important to conduct thorough research and due diligence when selecting AI tools. We do not endorse or promote any specific AI tools mentioned here. This article is for educational and informational purposes only. It is not intended to provide legal, financial, or clinical advice. Always comply with HIPAA and institutional policies. For any decisions that impact patient care or finances, consult a qualified professional.
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1. Give Hard Problems a Few Minutes Before You Reach for AI
In April 2026, researchers from Carnegie Mellon, Oxford, MIT, and UCLA released a preprint. That’s a paper shared publicly before it goes through peer review.
It described a series of randomized controlled trials with 1,222 participants working through math and reading comprehension tasks. Some had AI help available. Others didn’t.
Here’s the thing. The researchers weren’t only measuring whether AI helped in the moment. They wanted to know what happened after the AI was taken away. While people had AI, they performed better. No surprise there. The surprise came next.
Once the AI was gone, the people who’d been using it did significantly worse on their own. They were also more likely to give up on difficult problems altogether. And that drop showed up after roughly ten minutes of AI-assisted work. Ten minutes!
The authors explain it by comparing AI to a good mentor. A good mentor will sometimes hold back the answer, because working through the problem is the whole point.
AI tools, as the authors describe them, are tuned to hand you a complete answer right away. Outside of safety limits, they almost never say no. Their hypothesis is that this trains you to expect instant answers. And that leaves you with less patience for problems that don’t give way right away.
So does this mean you should avoid AI for hard problems? No.
It means that the next time a task without AI feels unusually frustrating, it’s worth asking whether a recent AI session is part of the reason. The task itself may not be as hard as it feels.
And every so often, try working through something difficult before you reach for AI, even when it’s right there. It’s a pretty straightforward way to keep that persistence in practice.
If you’ve ever felt your patience for a tough problem slipping and couldn’t figure out why, this might be part of the answer.
2. Hand Off the Work, Then Question What Comes Back
You’ve probably heard that using AI regularly wears down your critical thinking.
A study published in March 2026 in the International Journal of Educational Technology in Higher Education complicates that story.
The researchers surveyed 912 business-school students in China, Europe, and the United States. They checked in at three points, about two weeks apart.
They looked at two things students do with AI. One was critically evaluating what it produces. The other was strategically handing tasks off to it. The researchers expected those two to pull against each other.
They didn’t.
Students who treated AI as a working partner reported more of both. And both were linked to stronger self-reported learning. Even delegation, which the authors had predicted would hurt, was positively associated with learning. That link was strongest at higher levels.
In fact, the most common pattern among students reporting the deepest learning was heavy delegation paired with active scrutiny of what came back.
Two caveats matter here.
First, the participants were business-school students. Second, the outcome was self-reported, not a test of reasoning.
So the study doesn’t show that one style of AI use protects your thinking skills and another erodes them. What it supports is narrower. Handing work to AI and questioning it aren’t an either/or.
Think about what that looks like in practice.
You can ask AI to draft something, then read it closely, question its assumptions, and decide whether it’s actually right. Or you can accept the draft because it sounds confident and well-organized. From the outside, those two look identical. They save you about the same amount of time. But they’re different acts.
In one, AI is doing your thinking for you. In the other, AI is giving you something to think about.
For decisions that matter, like a diagnosis, a financial commitment, or advice you’re giving someone else, the more effortful version is worth the extra few minutes. Even when the easier one is sitting right there.
3. Get a Second Opinion When AI Agrees With You
This might be the most surprising finding of the three.
A study published in Science in March 2026, led by researchers at Stanford, measured something called sycophancy. That’s the tendency of AI systems to affirm and agree with what you say instead of pushing back.
The team tested eleven widely used AI models. They compared the models’ answers with human responses to the same advice-seeking prompts. On average, the models endorsed the person’s actions 49% more often than humans did. That included prompts describing deception, illegal conduct, or other harm.
One test used posts from a Reddit forum where people describe interpersonal conflicts and ask for a verdict. In posts where the community had unanimously judged the poster to be in the wrong, the models still sided with the poster in 51% of cases. Let that sink in for a second.
Then the researchers looked at what this does to people.
Across three preregistered experiments with 2,405 participants, a single validating AI reply left people less inclined to own their part in a disagreement or try to mend it. It also made them more certain they’d been right.
According to Stanford’s summary of the research, some participants worked through pre-written dilemmas based on the forum posts. Others discussed a conflict from their own lives.
And here’s where it gets tricky. Participants rated the agreeable replies as more trustworthy. They were also more willing to come back to them.
The authors argue that this gives developers a commercial reason to leave the behavior in place. Think about that for a minute. The thing that makes an AI reply feel good is the same thing that keeps you coming back, whether or not it’s steering you well.
And it’s pretty easy to see how it plays out. You describe a situation from your side, which is the only side you can describe. The AI tells you you’re right. You walk away feeling better and a little more dug in.
So the habit worth building is a specific kind of skepticism, aimed at AI’s agreement rather than its facts. When AI validates your decision, your draft, or your side of a disagreement, that validation isn’t neutral information. It’s coming from a system with a measured tendency to side with the user. And in the study, people preferred that tendency even as it skewed their judgment.
If you’re dealing with a real conflict with someone, a business decision that affects other people, or a moment of genuine self-doubt, talk to an actual person too.
A second opinion from a human carries information that AI agreement often doesn’t.
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Keep Using AI, Just Know What It’s Doing
Each of these studies has limits, from who was studied to how the outcomes were measured. They’re worth reading in the originals. None of them makes a case for abandoning AI.
That said, the sycophancy researchers are explicit that the effect they measured is harmful. And the study’s lead author has cautioned against using AI as a stand-in for people when you’re working through interpersonal problems.
The answer is awareness.
AI tools tend to be fast, complete, and agreeable. The research above suggests those same qualities can sometimes work against you. Knowing that isn’t a reason to be suspicious. It’s useful context.
You don’t need to second-guess every answer AI gives you. You just need to know which way it tends to lean. It can change how you read your own frustration, your own confidence, and your own certainty that you were right, the next time any of those show up in an AI conversation.
So which of these three have you noticed in yourself? We’d love to hear it so share it in the comments!
Download The Physician’s Starter Guide to AI – a free, easy-to-digest resource that walks you through smart ways to integrate tools like ChatGPT into your professional and personal life. Whether you’re AI-curious or already experimenting, this guide will save you time, stress, and maybe even a little sanity.
Want more tips to sharpen your AI skills? Subscribe to our newsletter for exclusive insights and practical advice. You’ll also get access to our free AI resource page, packed with AI tools and tutorials to help you have more in life outside of medicine. Let’s make life easier, one prompt at a time. Make it happen!
Disclaimer: This article is for general informational and educational purposes only. It does not constitute medical, legal, compliance, or professional advice. The information provided here is based on available public data and may not be entirely accurate or up-to-date. It’s recommended to contact the respective companies/individuals for detailed information on features, pricing, and availability.All screenshots, if any, are used under the principles of fair use for editorial, educational, or commentary purposes. All trademarks and copyrights belong to their respective owners.
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If you are looking for soaring consumer stocks you can actually hold, forget about, and think about in seven years, it helps to start with names that already look too obvious and then ask what most people are missing. Two that fit that mold for me right now are The Coca‑Cola Company (KO +0.01%) and Costco Wholesale (COST -0.91%). Both companies and their stocks are already widely followed, but there are still some lesser-known angles that make them worth watching and help explain why investors remain interested.
Image source: Getty Images.
Coca‑Cola: branding to combat health traffic
You might look at Coca‑Cola and think it is a slow, sugary beverage company that will get chipped away by health trends and new brands. The numbers from this year tell a different story. In the second quarter of 2026, Coca‑Cola reported global unit case volume growth of 5%, net revenue up 7%, and operating income up 9%, then raised full‑year guidance. This shows that the business is not stuck in neutral.
I’m not much of a branding enthusiast. I think brands like Coca-Cola already have pricing power without needing to change much, but in July, Coca‑Cola rolled out a new global visual identity system across more than 200 markets, designed to make every can, cooler, and digital ad unmistakably Coca-Cola. At the same time, it is committing about $10 billion to U.S. production and distribution infrastructure through 2030. In the company’s own words, they are building out the infrastructure behind its systems through a new “Brand Center” and technology-powered Design Intelligence tools that provide its marketing and agency network with shared resources for managing and enforcing Coca-Cola’s visual identity at scale.
To me, that’s a forward-thinking move. Coca‑Cola is tightening its presence everywhere while deepening the physical network that gets drinks into coolers and restaurants. Over seven years, that kind of brand and logistics work is what keeps the company relevant even as tastes evolve. Add the company’s dividends to this, and it is a safe stock that will continue to soar.
Today’s Change
(0.01%) $0.01
Current Price
$88.10
Key Data Points
Market Cap
$379BMarket cap calculated using publicly traded shares outstanding only. Does not include unlisted, private, or dual-class non-traded shares. Implied market cap may vary.
Day’s Range
$88.10 – $89.36
52wk Range
$65.35 – $92.49
Volume
13.2M
Avg Vol
16.7M
Gross Margin
61.95%
Dividend Yield
2.38%
Costco: Low yield, high conviction
You might glance at Costco’s dividend yield and assume it is not worth holding for income, especially after a strong run over the last couple of years. The way management is treating cash and growth makes me see it differently. For the June 2026 retail month, Costco reported net sales of $29.24 billion, up 10.6% from a year earlier.
At the same time, Costco continues to open and remodel warehouses, investing roughly $6.5 billion a year to expand capacity and improve the member experience, according to company management. The warehouse additions get plenty of attention, but I don’t think investors fully appreciate how much revenue and membership growth each new location can add to the business, giving Costco another runway for growth as it expands its footprint. The regular dividend, recently raised to $1.47 per share, is only part of the story, as Costco has also used special dividends to return excess cash to shareholders while continuing to prioritize investments in the warehouse model.
So while you may think Costco is “too expensive with a tiny yield,” I think of it as a membership machine that keeps gaining scale, with a management team that treats growth and cash returns as two sides of the same coin. If you own it for seven years, you are betting that more households will choose Costco as their default place to stretch budgets and that you will share in both the earnings and the occasional big payout when cash piles up.
Update 9/24/26: 15% back deal is now available on U.S. Bank offers. Valid through 11/9/26. Minimum $60 payment and $27 max cashback.
The Offer
Check your Chase Offers for the following deal:
Earn 15% cash back on your new Optimum subscription when you spend $60 or more (including taxes and after any discounts). Max $26.75 cash back. Please note that this is for a subscription purchase.
The Fine Print
Offer expires 7/31/2026.
Offer valid for new customers only.
Offer valid one time only.
Must make first recurring payment by 7/31/2026.
Offer valid on first payment only.
Our Verdict
Seems to be widely available on all Chase cards with the exception of the INK Cash/Plus cards. This is an excellent deal for Optimum. Note, again, the fine print suggests this won’t work for existing users – I’d be curious to hear if anyone actually tries this out.
Also note, you might lose your autopay discount if you pay with the card; sometimes bank payment is required for that.
OpenAI is preparing to preview its latest cybersecurity-focused model, GPT-6 Cyber, in the coming months, according to multiple sources familiar with the plans. It will also unveil a new product to help customers deploy the model in a more secure, automated manner.
The new, yet-to-be-named product will be a first for OpenAI, and extends a paradigm that OpenAI pioneered with its consumer products, in which ChatGPT serves as a gateway through which many users access new models like GPT-6 Astra. It aims to help customers create automated workflows and patch vulnerabilities in the face of increasingly sophisticated, AI-powered cyberattacks. It also gives OpenAI more oversight into how its models are being used, to monitor for safety.
A limited number of customers in OpenAI’s application-only Daybreak Red program already have access to GPT-6 Cyber for alpha testing, the source said. Daybreak is the company’s cybersecurity program, which is broken into two access tiers—red and blue. Customers in the Daybreak Red program have access to OpenAI’s most advanced cybersecurity products. Daybreak Blue is its more generalized access program, though it is also application-only.
The release of the new cyber products comes as OpenAI and other leading AI labs have been under fire for a string of worrisome incidents in which “rogue” agents escaped their sandboxes and hacked outside websites including the Hugging Face site and an Australian government site. But while the incidents have set off alarms about AI’s security risks, OpenAI’s new cybersecurity tools are part of an ongoing effort by the company to develop AI security products.
GPT-6 Cyber is the fourth cybersecurity-focused model OpenAI has released this year. Its first was GPT-5.4 Cyber in April 2026, followed by GPT-5.5 Cyber in June, and GPT-5.6 Cyber in August. OpenAI has been focusing on enterprise sales of cybersecurity products, an effort now led by its Chief Revenue Officer Dali Rajic, who joined the company in August.
OpenAI said earlier this month it will invest $1 billion to subsidize the use of its cybersecurity products for critical services.
Next week, OpenAI also plans to ship a dozen or more other products at its annual DevDay event, set for Sept. 29, according to another source familiar with the program. Most of those releases are not related to cybersecurity but rather other areas of the business, both enterprise- and consumer-focused.
OpenAI has put a freeze on any major launches in the past 2 weeks, save for its affordability-focused GPT-6 Sol and Luna models, so it could ship them all at DevDay, the source said. Earlier this month, CEO Sam Altman teased the buffet of new releases at DevDay in a tweet with multiple ship emojis.
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