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Apple’s “Surprise and Shine” event on Wednesday was packed with new products, from the foldable iPhone Duo to an Apple Watch equipped with upgraded heart rate sensors. Apple also released the newest generation of iPhones, Apple Watches and AirPods.

The event, Apple’s biggest launch of the year, also signaled a shift in leadership. The company’s new CEO, former head of hardware engineering John Ternus, took over on September 1 and delivered the opening remarks at the event. He initially focused on AI and the standard it needs to meet to improve lives, from all-day battery life to an enhanced visual experience. 

“Today we’re going to take these abilities even further with the next generation of iPhone,” Ternus said at the event. 

Here’s what Apple announced.

iPhone Duo foldable phone

“Others have created foldables that feel like two screens stuck together,” Ternus said. “We started with the experience that we would want for ourselves.”

The iPhone Duo features a 5.4-inch front screen that transforms into a 7.6-inch screen when opened. You can angle the phone however you want, and the screen will adjust, opening up new possibilities for photos and videos. 

“When opened, it’s our thinnest iPhone ever,” Ternus said.

iPhone Duo brings an entirely new design to a familiar iPhone display. Its purpose is to give users a larger screen and a phone that can still fit in their pocket. It is also the first iPhone that is compatible with Apple Pencil, so users can annotate documents and highlight text. 

The new iPhone is made of titanium and is dust- and water-resistant.

“iPhone Duo is the most transformational change to iPhone since the original,” Ternus said.

For customers who are worried about the crease and how it will hold up over time, Apple’s chief hardware officer, Johny Srouji, explained that Apple precisely aligned each individual hinge for durability. 

The iPhone Duo starts at $1,999 with 256 GB of storage and is available in white and night sky (dark blue). Preorders start on October 16, and phones will ship starting on October 23.

iPhone 18 Pro and Pro Max

For those not yet ready to hold a foldable phone, Apple offers its latest Pro and Pro Max models. “We made massive advancements in the most important areas,” Ternus said of the iPhone 18 Pro, highlighting longer battery life and an improved camera.

The phone contains a new A20 Pro chip, which powers “massive advancements in the most important areas.” For example, the iPhone 18 Pro takes a “massive leap” in battery life. Due to the new chip’s efficiency, users get 36 hours of battery life on the iPhone 18 Pro and “longest battery life by far” on the 18 Pro Max with 45 hours.

The iPhone 18 Pro and Pro Max come in new colors, including glacier (light blue) and burgundy (dark cherry). The phones also contain “the most advanced camera” Apple has ever made, according to the presentation.

The iPhone 18 Pro costs $1,199 for 256 GB, while the iPhone 18 Pro Max starts at $1,299. The main differences between the phones are screen dimensions and battery life. The iPhone 18 Pro has a 6.3-inch screen, while the larger iPhone 18 Pro Max has a 6.9-inch screen.

Preorders open September 12, and shipping starts September 18. 

A new Siri

Siri was also due for an upgrade. The voice assistant now considers personal context and can search apps like Mail and Messages to find answers to queries. It works across 3,000 apps and is built into the Camera app on iPhone, so users can ask questions and take action more quickly. It also has a broader range of expressive voices, allowing users to personalize how human and emotive they want the voice to be. 

Users can also write and edit with Siri virtually anywhere they can type. For example, they can write an email to their child’s soccer coach while on the go. 

Siri is available in beta in English, with support for other languages coming next month. 

AirPods 5

Apple upgraded its popular AirPods with better noise-blocking features. The less expensive $129 model now has active noise cancellation, and the higher-end model that comes with a wireless charging case is $149. 

“We’re thrilled that with AirPods 5, we’re able to bring Active Noise Cancellation — one of our most beloved features — to our most affordable AirPods,” Dave Pakula, Apple’s vice president of Hardware Engineering, said in a press release. 

Apple Watch Series 12 and Ultra Watch 4

Apple also introduced the newest generation of Apple Watch, the Series 12, and revealed a new Health Sensing System. The company redesigned sensors to provide higher-frequency heart rate data. For example, the new watches measure heart rate data every five seconds, a 60-time frequency increase over previous models.

Apple tested the Apple Watch against other leading wearables in a clinical study, and “Apple Watch has the most accurate heart rate sensing in a variable,” according to the presentation. 

The company is also introducing a new Readiness score, which combines data points from heart rate data to provide a snapshot of health.

It also debuted a new feature called Audio Intelligence, which makes sense of what you hear. It uses Apple Intelligence to register sounds like alarms, sirens and doorbells. It also includes Siri Recap, which generates notes and transcripts from audio. Live Rewind is another new feature within Audio Intelligence. It allows users to go back 15 seconds to transcribe what someone just said.  

The Apple Watch Series 12 and Ultra 4, priced at $399 and $799 respectively, are available for preorder now. They both launch on September 18. The main differences between these two options are battery life and case materials. The Ultra 4 is built for more extreme conditions, with a titanium case and up to 50 hours of battery life, while the Series 12 comes in aluminum and ceramic with a standard all-day battery life. 

Apple’s “Surprise and Shine” event on Wednesday was packed with new products, from the foldable iPhone Duo to an Apple Watch equipped with upgraded heart rate sensors. Apple also released the newest generation of iPhones, Apple Watches and AirPods.

The event, Apple’s biggest launch of the year, also signaled a shift in leadership. The company’s new CEO, former head of hardware engineering John Ternus, took over on September 1 and delivered the opening remarks at the event. He initially focused on AI and the standard it needs to meet to improve lives, from all-day battery life to an enhanced visual experience. 

“Today we’re going to take these abilities even further with the next generation of iPhone,” Ternus said at the event. 

Golfing great Shane Lowry has won a Claret Jug, competed in Ryder Cups, and this year drained a hole-in-one at the Masters in front of a roaring crowd. But ask him about his proudest role, and he brings up his father Brendan, a former Gaelic football player, who needed both a hip and knee replacement. Shane took on the role and responsibilities of caregiver, and that experience is at the heart of his new partnership with Stryker, a global medical technology leader. 

The company’s mission, says Joint Replacement division president Katherine Truppi, is simple: “Together with our customers, we are driven to make healthcare better.” Truppi says the Lowry partnership was a chance to shine a light on an “under-recognized role” — the caregiver — and to help other families feel less alone navigating a similar journey. I caught up with Shane as he prepares to battle it out at the 2026 Irish Open to talk about his dad, preventative health, and what it actually feels like to make a hole-in-one on one of golf’s biggest stages.

Dan Bova: What drew you to this partnership with Stryker?
Shane Lowry: I’m in a fortunate position where I get the opportunity to meet so many people, and I get to pick the partnerships I choose to get involved with. This one for me was pretty straightforward — my dad had hip replacement surgery 10 or 12 years ago. His hip worked for a while and took pressure off his knee, but ultimately his knee was always the problem, and he ended up getting a knee replacement a few years ago. Both are Stryker products, and he’s still going pretty strong now.

A lot of us find ourselves in that “sandwich generation” — caring for aging parents while raising our own kids. What did it mean to be able to help your dad through this?
I’ve got my own 18-month-old, so I’m forging my own path, building my own life, and taking care of my own family. But I feel like I’ve been in a fortunate position where I can take care of my parents, too. When it came time for my dad to get something done about his hip, I was able to go find the right people. My dad’s still only 67 — he’s young, so he doesn’t need that much taking care of. But when you’re able to help him through tougher times, it’s pretty fulfilling, to be honest.

Men in particular aren’t always great about taking care of themselves and tend to put off procedures like this. What would you say to someone who’s putting it off?
There’s nothing wrong with going and getting a consultation and seeing how much it can help you. Because when you do that, you’ll realize you can go from not being able to do simple everyday jobs — my dad used to have trouble tying his shoelaces — to being back out there. As you get older, you want to be out and about with your grandkids, kicking a ball, playing golf. I think the hardest part for most people is the original step toward the consultation and starting the ball rolling. But once you do that, you realize it’s the right thing for you.

What do you say to entrepreneurs reading this — hard-charging people working a million hours, probably not eating great, probably not exercising as much as they should?
It’s hugely important to take care of yourself, your body and your mind. A small bit of exercise and eating the right stuff and other stuff in moderation — you need to enjoy yourself at times too — but it’s very important to take care of yourself. I think as I’ve gotten older, having kids, I’ve realized I want to stay younger for longer. And I think if you have a friend or family member and you see them limping or struggling through everyday life, don’t be afraid to say something. Don’t be afraid to ask, “Do you think you should get this checked out?” 

We’ve talked a lot about physical struggles — let’s talk about something a little more fun. What does it actually feel like to hit a hole-in-one?
It’s a funny thing, because you’re obviously aiming there, right? That’s the object of golf — get the ball in the hole as quickly as you can. But you don’t stand up on a hole and go, “Right, I’m going to make a hole-in-one here.” You’re trying to hit the best shot you can, and sometimes it just comes off. I’ve been fortunate to make a few really good ones — most recently this year at the Masters, on the Saturday afternoon, playing with one of my good friends, I made a hole-in-one on the sixth. To put myself right into contention at one of the biggest tournaments in the world — there aren’t many better feelings, to be honest with you. It’s a funny thing too, because when it happens in the middle of your round, your adrenaline goes through the roof, and you actually spend the next twenty minutes trying to get your heart rate back down, because you’ve still got a lot of golf to play. But it’s a very cool thing to have 20,000 people there cheering you on. 

Golf, like entrepreneurship, has a lot of highs and lows. What have you learned about staying even-keeled through it all?
It’s an interesting sport we play because it’s such a long career, and I think it’s pretty similar to everyday life — nothing is plain sailing. It’s full of ups and downs, highs and lows, and it’s important to try and be as even as you can through it all. The last few months haven’t been the best for me, and I think it’s important to never lose sight of your goals or what you’re working toward — just keep grinding through, day by day, and eventually it’ll turn. It’s a stressful job at times, but it’s an amazing job. I’m very lucky to do what I do. I love competing at the highest level — it’s what I get out of bed for.

Golfing great Shane Lowry has won a Claret Jug, competed in Ryder Cups, and this year drained a hole-in-one at the Masters in front of a roaring crowd. But ask him about his proudest role, and he brings up his father Brendan, a former Gaelic football player, who needed both a hip and knee replacement. Shane took on the role and responsibilities of caregiver, and that experience is at the heart of his new partnership with Stryker, a global medical technology leader. 

The company’s mission, says Joint Replacement division president Katherine Truppi, is simple: “Together with our customers, we are driven to make healthcare better.” Truppi says the Lowry partnership was a chance to shine a light on an “under-recognized role” — the caregiver — and to help other families feel less alone navigating a similar journey. I caught up with Shane as he prepares to battle it out at the 2026 Irish Open to talk about his dad, preventative health, and what it actually feels like to make a hole-in-one on one of golf’s biggest stages.

Dan Bova: What drew you to this partnership with Stryker?
Shane Lowry: I’m in a fortunate position where I get the opportunity to meet so many people, and I get to pick the partnerships I choose to get involved with. This one for me was pretty straightforward — my dad had hip replacement surgery 10 or 12 years ago. His hip worked for a while and took pressure off his knee, but ultimately his knee was always the problem, and he ended up getting a knee replacement a few years ago. Both are Stryker products, and he’s still going pretty strong now.

Opinions expressed by Entrepreneur contributors are their own.

When TikTok exploded, Instagram had a problem. Short-form video was changing how people consumed content, and Instagram needed an answer.

Maria Zhang, now CEO of Palona AI, was part of the team working through that challenge.

“It was quite intense,” Zhang says. “TikTok just went wild.”

Zhang joined Facebook, now Meta, as vice president of engineering at Instagram. During her time there, the platform faced fierce competition from TikTok and launched Reels.

“It wasn’t a straight shot,” Zhang says. “We definitely iterated a ton and made tough decisions along the way.”

At the time, Zhang wrote a white paper outlining what she believed would help Instagram compete.

“To win against TikTok, the secret sauce is AI,” she says.

AI could understand user interests, identify trending content and emerging creators, and recommend the right content at the right moment. It wasn’t Zhang’s first experience seeing AI work at massive scale. Before Meta, she served as vice president of engineering at Yahoo and later CTO of Tinder, where she watched the dating app experience what she describes as “hockey stick” growth.

Her team at Tinder used AI for content moderation, matching, recommendations and ranking, earning an award for AI innovation in 2017. Later, at Google, Zhang worked on technology designed to improve developer productivity.

Each experience gave Zhang another look at what happens when powerful technology is applied to a difficult problem.

Now, she believes the industry is at the beginning of something much bigger.

“As a technologist, I see this wave of transformation as the most impactful,” Zhang says. “Many, many times — bigger than internet and then the iPhone came out, mobile internet.”

That left Zhang with a different question: Where could everything she had learned about AI make the biggest difference?

Building restaurant intelligence

After years of building technology at some of the biggest companies in the world, Zhang started thinking about where AI could make the biggest difference.

Google engineers weren’t at the top of her list.

“We can help Google engineers be more productive, but I think they don’t need a lot of help,” Zhang says.

Zhang and her co-founders wanted to apply what they had learned somewhere else. They chose restaurants.

“You guys are absolutely the hardest working people,” Zhang says. “And there are many, many of you guys.”

What Zhang found was an industry where employees serve the customer in front of them while answering phones, managing takeout orders and handling larger opportunities like catering.

A Father’s Day test at Cali BBQ showed how much activity could be hiding in those interruptions.

The restaurant let Palona AI handle incoming calls rather than sending them to employees. Roughly 350 calls came in that day.

“You’re like, ‘I never knew so many people call me,’ because the lines get busy and you never even picked up,” Zhang says.

Customers wanted to know about tables, hours and whether ribs and brisket were still available. Zhang says takeout orders doubled and Cali BBQ finished the day with 18% year-over-year top-line growth.

But the experiment exposed another problem.

“A lot of the calls were actually for large orders,” Zhang says. “Catering.”

Catering inquiries can involve budgets, guest counts, proposals, changes and follow-ups. Zhang saw another place where AI could take work off a restaurant manager’s plate.

Her team built an AI catering manager to handle those interactions. Zhang says one restaurant chain generated $5,800 through the system in a single day.

For Zhang, that gets back to why she left Big Tech. The opportunity wasn’t simply to build more AI. It was to find places where technology could give people back time to focus on work that still needs a human.

About Restaurant Influencers

Restaurant Influencers is brought to you by Toast, the powerful restaurant point-of-sale and management system that helps restaurants improve operations, increase sales and create a better guest experience. Toast — Powering Successful Restaurants. Learn more about Toast.

Restaurant Influencers is proud to have PepsiCo as a sponsor of this episode. Partnering with PepsiCo Foodservice helps restaurant operators drive sustainable growth through smarter digital experiences, AI-backed menu optimization, and tools designed to create more profitable online orders. Check out PepsiCo Foodservice

I’ve had conversations with so many people who have built software in the past year, and I’m not just talking about engineers. I’m talking about people across a variety of professions and walks of life, many of them with no formal engineering experience beyond their own curiosity and experimentation.

A few years ago, that would have been unthinkable. But AI has completely changed what’s possible and who it’s possible for. If I could sum up the change in one distinct sentence, it’d be this: AI has collapsed the distance between idea and execution.

When it comes to everyday people vibe-coding a fun app into existence, this is a truly exciting development. But it’s also forced us to re-interrogate one of the most central questions at the heart of business technology: Should we build it, or should we buy it?

That question is one of the many things that AI has changed forever.

The build vs. buy conversation, then vs. now

For most of my career, build vs. buy was mostly a capability question. Could your team actually construct and launch the software you need? Did you have the engineers, the time and the technical depth to pull it off?

The reason to build it yourself was simple: You’d be able to configure the software to fit your company’s hyper-specific needs.

The alternative, buying software from a trusted vendor, was the faster and safer path. You might not get a tool that’s been 100% custom-fit to your company and your company alone, but you got a solution you could rely on — one that wouldn’t take months to deploy and exorbitant costs to maintain.

In short, the “build it ourselves” path used to be a long, arduous one, full of hurdles that some companies were willing to navigate for the tailor-made solution waiting on the other side. 

Now, the road looks a lot less daunting on its surface. In most cases, AI has answered the “can we build it?” question for you. The harder question is now “should we build it?”

I’ve seen a lot of companies make a critical error when they answer this question. They see how much smaller the hurdles to deploying homemade software have gotten. And they underestimate the risks that running their homemade software creates.

What building it yourself can cost you

The capability question may be settled, but the responsibility question isn’t. And before you decide to build software internally, you have to consider the financial and reputational costs you’ll be responsible for.

First, there’s the issue of reliability. Your homemade solution might perform perfectly in a demo. But running software that customers rely on is a different story. It has to keep running perfectly at three in the morning, every night, for as long as your business exists. It needs to hold up under unexpected volume. It requires entire teams of people whose job it is to make sure nothing goes down, and other teams ready for when something does.

Because when something inevitably does go wrong, you won’t have a vendor to call for help, with their own dedicated teams who fix problems 24/7. You’ll only have your own people and your own resources.

Then there’s the ongoing cost of maintaining what you’ve built. Using AI to build a product might seem easier than it used to be, but running a serious AI-powered product isn’t cheap. And that cost doesn’t stop the day you ship.

Then there’s a much subtler cost: You lose the compounding value of everybody else’s experience. If you use a vendor’s product, that product will improve because thousands of other customers are using it, hitting edge cases, raising new questions and giving unique feedback. Build it yourself, and you’re on your own island, evolving only as fast as your own team can identify areas for improvement.

And last but certainly not least, there are the worst-case scenarios that none of us like to think about. You build your own software, and something goes catastrophically wrong — like your database getting corrupted or even completely deleted by some misconfigured AI. This isn’t a hypothetical; these stories have happened. 

As the CEO of a software company, I know firsthand that trusted vendors have a rigorous and expensive process for ensuring their data, and their customers’ data, remains safe, secure and protected from the aforementioned scenarios. If you build something yourself and don’t take the same steps, you’re risking catastrophe.

Customer-facing systems are a different category of risk

Of course, not every build carries the same stakes. I’ve seen teams have great success building things like internal dashboards: low-risk, custom-fit to exactly how they work and entirely internal. If something breaks, the blast radius is exceptionally small. They fix it as quickly as they can and move on.

Customer-facing technology does not offer that kind of grace period.

I run a company in the CX space, where the stakes are high. If you build your own customer service tool and it fails, it doesn’t fail quietly. It fails for the customer who needed help and didn’t get it, at the exact moment your business was supposed to show up for them. That’s not a bug you patch overnight or a mistake you chalk up to a “learning experience.” It’s trust you never get back.

The question isn’t just whether you can build something that works. It’s whether you can build something that never fails, because you can’t afford it to.

Today’s build vs. buy debate requires specific rules and guardrails

None of this means your teams should stop building things themselves. AI has opened up a genuine world of experimentation, and your engineers should be encouraged to explore it. But freedom without guardrails is how companies end up in trouble.

The rule I’d offer is simple. Experiment and build for the things that are low-stakes and safely contained inside your own walls. Many of these experiments will break. And when they do, the damage stays small, and you learn something in the process.

Customer-facing technology requires a completely different philosophy. The safety of your customers’ data and the trust they have in your business is at stake 24/7. 

A trusted vendor with its own security, compliance and infrastructure teams has spent years, and a lot of money, proving it can carry that weight. You can’t replicate that kind of trust with a few weekends of vibe-coding or even a few months of dedicated engineering time.

The companies that get this right are the ones that know where to draw the line. They’re the ones that encourage internal innovation within safe guardrails. And they also know when to rely on proven vendors who can not only customize solutions to their needs, but also bring the reliability, security and hard-earned trust that customer-facing technology requires.

I’ve had conversations with so many people who have built software in the past year, and I’m not just talking about engineers. I’m talking about people across a variety of professions and walks of life, many of them with no formal engineering experience beyond their own curiosity and experimentation.

A few years ago, that would have been unthinkable. But AI has completely changed what’s possible and who it’s possible for. If I could sum up the change in one distinct sentence, it’d be this: AI has collapsed the distance between idea and execution.

When it comes to everyday people vibe-coding a fun app into existence, this is a truly exciting development. But it’s also forced us to re-interrogate one of the most central questions at the heart of business technology: Should we build it, or should we buy it?

For most investors, the “market” is whatever shows up on the CNBC ticker. But that “visible market” is only part of the story. Today, more than 99% of U.S. companies are privately held, and many of the most transformative businesses of the last two decades created substantial value long before they ever reached the public markets — if they reached them at all.

That shift has changed the way many entrepreneurs think about investing. Increasingly, founders and business owners aren’t just looking to public markets to grow wealth. They’re looking toward private capital — not only as investors seeking returns, but as operators who understand firsthand what it takes to build enduring businesses.

And while private capital has historically been associated with large institutions and ultra-wealthy families, the underlying principles behind it are surprisingly straightforward. At its core, private capital is about patience, access and active value creation.

Why are more entrepreneurs investing beyond public markets?

One of the defining characteristics of private capital is illiquidity. Unlike public stocks, private investments are often held for seven years or longer. That may sound like a disadvantage in a world obsessed with flexibility and instant liquidity.

But illiquidity can also create opportunity.

Markets have historically rewarded investors willing to commit capital over longer periods of time. In finance, this is often called the “illiquidity premium” — the idea that investors may earn higher returns in exchange for giving up daily access to their money. Entrepreneurs intuitively understand this concept because they’ve lived it.

No founder expects to build a meaningful company in a quarter or two, or even a year. Building enterprise value takes time, discipline and the ability to weather volatility without reacting emotionally to every headline.

Private capital investing often rewards the same mindset. And the math of compounding can become meaningful over long periods. A modest return advantage sustained over decades can create dramatically different outcomes for families, foundations and future generations.

What do private capital investors look for before investing?

Many people assume private capital investing is about searching for the next Nvidia. In reality, experienced investors often spend just as much time thinking about downside protection as upside potential. The best private market investors tend to focus on a few core questions:

What makes a private company attractive to investors?

Great private investments are often less about excitement and more about resilience. Investors want businesses that can survive economic cycles, adapt to change, and continue generating cash flow under pressure.

That’s one reason many long-term investors avoid overly speculative sectors or businesses built entirely on momentum.

Why does management quality matter so much in private markets?

In public markets, investors typically buy shares and hope management performs well.

In private markets, investors frequently have influence or control. They can improve operations, strengthen leadership teams, optimize capital structures, or help businesses scale strategically. That operational involvement is one reason private investors believe they can generate returns above public market equivalents.

How do investors evaluate whether a market is overheated?

One of the paradoxes of investing is that once everyone becomes excited about an asset class, returns often compress.

Private credit is a good recent example. Tremendous amounts of capital have flowed into the space over the past several years, creating more competition and, in some cases, lower prospective returns.

Experienced investors constantly ask not only whether an opportunity is attractive, but whether too much capital is chasing the same idea.

Why does manager selection matter in private equity and venture capital?

Manager selection matters enormously in private markets.

Unlike public investing, where performance differences between managers may be relatively narrow, private market outcomes can vary dramatically depending on who is deploying the capital. The challenge is that many top-performing funds are capacity constrained or closed to new investors altogether. Access, relationships and diligence become critically important.

Why are entrepreneurs often strong private capital investors?

Entrepreneurs often have an advantage in understanding private capital because they understand how businesses are actually built. They know growth is rarely linear. They know great businesses often look messy in the early years. And they know meaningful value creation usually happens quietly, long before broader markets recognize it.

That perspective can make founders particularly thoughtful long-term investors.

Many entrepreneurs are also increasingly motivated by something beyond returns alone. They want to invest in innovation, help emerging businesses grow, support sectors they believe in or create opportunities for the next generation. In that sense, private capital can become a way of paying forward the entrepreneurial ecosystem itself.

Key takeaways for first-time private capital investors

Private capital can be compelling, but it also requires discipline. For investors considering the space, a few principles matter:

Private investments should complement a portfolio — not dominate it

Illiquidity is manageable until it isn’t. Even sophisticated institutions occasionally discover they’ve committed too much capital to long-duration investments. The strongest private capital strategies are integrated thoughtfully alongside public market exposure, liquidity needs and long-term family goals.

Diversification matters as much in private markets as it does in public ones

Private investing is not about finding one perfect company or one breakthrough technology. It’s about building exposure across managers, industries, vintages and asset classes over time. The best private capital portfolios are typically built patiently and intentionally — not opportunistically.

Complexity is part of the tradeoff

Private investments often involve capital calls, K-1s, delayed reporting and long holding periods. Investors should enter the space with realistic expectations about operational complexity and liquidity constraints.

There is also real risk in chasing trends, overpaying for growth or investing in overcrowded sectors where too much capital has flooded the market. Private capital is not a shortcut to wealth. Done well, it is usually the opposite: a disciplined, long-term process.

Patience is often the real differentiator

Perhaps most importantly, private capital investing requires emotional discipline. These investments are designed to compound quietly over time, not provide daily feedback. That can feel uncomfortable in a culture conditioned for constant visibility and instant results. But some of the most meaningful opportunities in investing — and in entrepreneurship — exist beyond the visible market.

For most investors, the “market” is whatever shows up on the CNBC ticker. But that “visible market” is only part of the story. Today, more than 99% of U.S. companies are privately held, and many of the most transformative businesses of the last two decades created substantial value long before they ever reached the public markets — if they reached them at all.

That shift has changed the way many entrepreneurs think about investing. Increasingly, founders and business owners aren’t just looking to public markets to grow wealth. They’re looking toward private capital — not only as investors seeking returns, but as operators who understand firsthand what it takes to build enduring businesses.

And while private capital has historically been associated with large institutions and ultra-wealthy families, the underlying principles behind it are surprisingly straightforward. At its core, private capital is about patience, access and active value creation.

Apple’s “Surprise and Shine” event on Wednesday is shaping up to be one of its busiest launches in years. 

According to Tom’s Guide, Apple will reportedly introduce three new iPhones at the event. The centerpiece could be Apple’s long-rumored foldable iPhone, widely expected to carry the iPhone Ultra name. The phone is rumored to use a book-style design with a 7.8-inch internal display and 5.5-inch outer screen. It will allow Apple to enter a foldable market that Samsung and other Android manufacturers have already spent years developing. 

The Ultra could be a major statement product but is likely an expensive one. Tom’s Guide reports estimated prices ranging from $2,000 to $2,500 and warns that availability may be limited at launch.

The other two iPhones Apple is expected to introduce are the iPhone 18 Pro and Pro Max. Both models are rumored to run on Apple’s upcoming A20 Pro chip. The phones may look similar to the prior Pro generation, but with a smaller Dynamic Island and a better front-facing camera.

Expected price hikes

A report last month from Counterpoint Research predicted that the iPhone 18 Pro models would cost $250 to $350 more than the existing iPhone 17 Pro lineup. The current iPhone 17 Pro Max costs $1,599; the iPhone 18 Pro Max could cost between $1,849 and $1,949. 

“A price increase on the new iPhones is inevitable,” the Counterpoint Research team wrote in the report. “The question is not whether Apple passes it on, but how large the final price bump is.”

Bloomberg recently reported that Apple will not introduce the standard iPhone 18, iPhone 18 Plus and a new iPhone Air at the “Surprise and Shine” event. Apple is reportedly reserving the event for higher-priced devices, while saving lower-priced models for a later release date. 

Other product updates

Apple will reportedly launch updates to the Apple Watch at Wednesday’s event. The company could show the Apple Watch Series 12 and Apple Watch Ultra 4, with faster chips, new health features and possible design changes. The watches will likely come with new colors and ceramic cases. 

Apple is additionally rumored to announce a new generation of AirPods. Tom’s Guide reports that possible upgrades include a newer chip, on-ear volume controls and health-oriented sensors.

According to Bloomberg, Apple is gearing up to release new devices and enter new product areas this year, including a new smart home hub with a 7-inch screen. Apple is also planning to introduce a new version of the Apple TV 4K streaming box, which hasn’t had an upgrade since 2022. 

A new chapter

Apple has a new CEO, former head of hardware engineering John Ternus, who took over on September 1. Ternus will lead the event on Wednesday. 

In a leaked memo to staff on his first day as CEO, Ternus said he was “so excited about everything we have in store.”

“We have a huge launch next week that’s going to be phenomenal,” he wrote. “Thanks for everything you’ve all done to make it possible.”

Apple’s “Surprise and Shine” event on Wednesday is shaping up to be one of its busiest launches in years. 

According to Tom’s Guide, Apple will reportedly introduce three new iPhones at the event. The centerpiece could be Apple’s long-rumored foldable iPhone, widely expected to carry the iPhone Ultra name. The phone is rumored to use a book-style design with a 7.8-inch internal display and 5.5-inch outer screen. It will allow Apple to enter a foldable market that Samsung and other Android manufacturers have already spent years developing. 

The Ultra could be a major statement product but is likely an expensive one. Tom’s Guide reports estimated prices ranging from $2,000 to $2,500 and warns that availability may be limited at launch.

This is the first piece in a series I am calling The University Intrapreneur. I have spent 20 years inside innovation programs at companies and universities on six continents, and I have watched the same failure happen every time an institution waited for permission it was never going to get.

AI is disrupting education. Most institutions have not caught up, and I put the reason down to arithmetic. A new degree program can take up to 18 months to move from proposal to approval, and a tenure-track faculty search runs 9 to 12 months from posting to a start date. Those timelines protect quality, and they were built for a world where the job a graduate walked into looked the same at the end of the process as at the start.

That world is gone, and no policy closes the distance, because policy moves at the speed the institution already moves. Only people can close it, the ones willing to build inside the cycle while the cycle is still running its slow vote.

Who drives innovation inside a university?

The university intrapreneur can be anybody. The role usually lands on a mid-level faculty or staff member who found a real problem and built a working answer on borrowed time, but it carries no fixed title and no fixed department. The org chart does not account for that person, the budget has no line for the work, and the institution’s ability to change depends on them anyway.

Gifford Pinchot III coined the word intrapreneur in a 1978 white paper written with Elizabeth Pinchot, and called them dreamers who do. Pinchot was writing about corporations, and the university version carries more weight now, because the distance they absorb is wider.

Anyone can be this person: faculty, staff, a department administrator, someone in the library. Most of them already have the talent. What they need is a name for the role, a tool built for the problem in front of them and an institution willing to give support and then step out of the way.

Can a university actually move this fast?

Yes, at a scale that should embarrass anyone who says a campus cannot move. The GI Bill put about eight million veterans through education, and by 1947, half of American college students were veterans.

UTeach, the smaller version of the same instinct, started as one faculty-built route at the University of Texas at Austin in 1997 and now runs at more than 40 universities, years before anyone wrote it into a plan.

Why can’t this wait another year?

More than a third of entry-level jobs now require AI skills, according to the National Association of Colleges and Employers, nearly triple the share that said so in the fall of 2025. That did not take five years. It took two semesters, one hiring cycle, the length of a single academic year.

A university that reviews curriculum on a seven-year cycle cannot answer a demand curve that moves that fast through a committee. It can only answer it through people already inside the building who build before the committee meets. Every graduate walking across the stage this spring is being measured against a bar that moved twice since they declared their major.

I hear the same objection from the hardest AI skeptics on every campus, and I take it seriously: A tool is not a strategy, and adoption numbers are not the same as judgment. They are right about that. But this argument has never been about the tool. It is about whether the institution around the tool can still change shape when the world outside it does. A university that cannot produce people willing to build ahead of policy will lose to one that can, with or without AI in the room.

What can you do this month? 3 moves, in order.

1. Name the role, then find the people already doing it, and name them where others can hear it. Nobody volunteers for something with no name, and nobody keeps building something nobody has celebrated. They come from anywhere: faculty, staff, students. Look for the unofficial tool half a department relies on, the pilot that outlived its funding, the student club that solved something the provost’s office is still studying.

2. Build the channel before you build the lab. One shared, visible place, open to faculty, staff and students alike, where builders say what they are working on before it is finished. Communication is what actually connects them: The campus that talks to itself catches two departments building the same project in parallel before either runs out of runway. Keep the bar to enter low, and give whoever uses it air cover — a named senior sponsor and one sentence you will repeat unchanged when someone objects.

3. Put money behind experimentation, not just permission. AI has cut the cost of standing up a pilot low enough that a department can fund one out of its own discretionary budget instead of waiting a year for a line item. Name a person who can approve that spend without a committee, and put a decision date on the calendar beside their name. A review date lets everyone postpone without feeling like they said no; a name attached to a date forces a yes or a no.

I learned this winning recipe directly, working on measuring AI impact within the California State University system, the nation’s largest public university system and its largest AI deployment, 22 universities and more than 471,000 students. The CSU surveyed its own community in the fall of 2025, with more than 94,000 respondents across students, faculty and staff, the largest study of its kind in higher education. Ninety-five percent of respondents had already used an AI tool. Eighty-two percent of students called AI essential to their profession, and the same share worried about their job security.

Nobody assigned that adoption. It happened because individual people decided the wait was more dangerous than building ahead of policy. Academia has always produced pioneers first and permission second, and I have watched the same pattern repeat on every continent I have worked. The pressure AI puts on a university does not get absorbed by a task force. It gets absorbed by a person, or it does not get absorbed at all.

That is the whole argument of this series. The people best positioned to rebuild a university’s capability are already inside it — not a vendor, not a consultant brought in for a semester. Our job, as leaders, is to find them and connect them to each other before someone outside the building does it instead.

The institutions that survive this decade will not be the ones with the most AI tools installed. They will be the ones that kept producing people willing to build before they were told to.

I am collecting these stories for the rest of this series: the builders nobody has named yet. If that is you, or you know who it is on your campus, tell me. I want to hear it, and I am easy to find.

This is the first piece in a series I am calling The University Intrapreneur. I have spent 20 years inside innovation programs at companies and universities on six continents, and I have watched the same failure happen every time an institution waited for permission it was never going to get.

AI is disrupting education. Most institutions have not caught up, and I put the reason down to arithmetic. A new degree program can take up to 18 months to move from proposal to approval, and a tenure-track faculty search runs 9 to 12 months from posting to a start date. Those timelines protect quality, and they were built for a world where the job a graduate walked into looked the same at the end of the process as at the start.

That world is gone, and no policy closes the distance, because policy moves at the speed the institution already moves. Only people can close it, the ones willing to build inside the cycle while the cycle is still running its slow vote.

According to the 2025 Google DORA report, 90% of developers now use AI daily and agree it makes their flow more efficient. Yet the same report says AI just amplifies what already exists in your business’ flow rather than making development stronger by default. When code becomes cheap, it’s so much easier to test each new idea without giving a proper quality estimation. That’s where product judgment becomes critical, picking the right problem to solve, testing the idea early, keeping the product lean, and knowing when to stop with new features.

To keep judgment ahead of production volume, business leaders can rely on five core principles.

Data from CB Insights covering over 400 closed venture-backed startups shows that 43% fail due to a lack of product-market fit. For most of them, the real problem was not the engineering capacity, but a clear understanding of what to build.

When a customer asks for a feature, they usually describe a quick fix that sounds good to them, cutting out of the loop the actual problem. If a support team asks for a button to pull all customer data into one screen, the real problem might simply be that searching for information takes too long. Before taking any request, word the core problem and confirm it with the person asking. A quick call to see how they currently solve the issue usually reveals far more than the request itself.

The Stack Overflow Developer Survey 2025 shows that 66% of developers spend extra time fixing “almost correct” AI code. At the same time, GitClear analyzed over 200 million lines of code and found an eightfold jump in duplication since AI tools went mainstream. It was often a question of price: whether to test new features or not. Now that AI has made development cheaper, weak ideas move just as fast as good ones unless you intentionally slow things down for a proper review.

Amazon learned this the hard way in December 2025 with Kiro, its internal AI assistant. Given broad access to fix a minor AWS billing dashboard bug, Kiro decided the cleanest solution was to wipe and rebuild the entire production environment. Result? A 13-hour standstill. The mess forced Amazon to freeze what AI tools could modify without human approval for 90 days. 

According to the Feature Adoption Report, around 80% of features in an average product are rarely or never used. Still, every unused button comes with a set of problems: it costs money to maintain, complicates onboarding, and needs to be fixed with version updates. With an AI speed it’s easy to send to a prod every technical possibility seen; what’s more, these might be the ones that don’t work properly. But a good product isn’t a feature count.  Before building something new, ask whether it strengthens your main product or just creates clutter. 

In 2026, Google quietly began winding down Firebase Studio, migrating users and key features into its broader suite of AI development tools. Instead of spreading resources on diverse platforms, Google chose to double down on its primary, high-impact tools.

Just because you can build a new feature fast, doesn’t mean you’ve learned a single thing about whether your users actually want it. MIT’s 2025 State of AI in Business study hit on this exact trap: 95% of AI pilots didn’t bring any measurable financial return, and only 5% made it to production with proven value. The product worked fine, but companies didn’t know how to measure the impact and learn on this data.

The key is in reviewing your funnel. Figma is using Figma Make to spin up fully interactive prototypes, validating concepts with real users before a single line of production code is written. It pulls product discovery right up to the decision-making stage, when failure is not that expensive and measurable. Stop judging your team’s success by how many features hit the roadmap each sprint. Pick the exact business metric you want to shift before building. If a new release doesn’t work out as expected, cut your losses, and don’t double down just because the AI made it easy to build.

Gartner projects that by 2027, half the companies that laid their teams off for AI will be rehiring again for those exact same roles once they’ll face the gap between efficiency metrics and real service quality.

The goal isn’t to see how much of your business you can automate; it’s to estimate where trust, review, and emotional involvement matter most. Leave all the mechanical routine to the machine and keep critical interactions human. This saved capacity is sure to bring both a better flow and experience.

AI doesn’t kill the need for great product strategy – it just highlights when you don’t have one. When building software becomes much cheaper, the final boss is not the speed but the confidence in strategy. Use the speed to test smarter, but never forget about the importance of human judgement.

According to the 2025 Google DORA report, 90% of developers now use AI daily and agree it makes their flow more efficient. Yet the same report says AI just amplifies what already exists in your business’ flow rather than making development stronger by default. When code becomes cheap, it’s so much easier to test each new idea without giving a proper quality estimation. That’s where product judgment becomes critical, picking the right problem to solve, testing the idea early, keeping the product lean, and knowing when to stop with new features.

To keep judgment ahead of production volume, business leaders can rely on five core principles.

Data from CB Insights covering over 400 closed venture-backed startups shows that 43% fail due to a lack of product-market fit. For most of them, the real problem was not the engineering capacity, but a clear understanding of what to build.

Many CEOs treat their company’s online search presence like a quarterly credit score — checking it periodically to ensure no major damage has occurred, then forgetting about it.  

Such a passive and defensive view misses how online searchers actually make decisions today, representing a fundamental misunderstanding of modern enterprise growth. When business-to-business (B2B) or direct-to-consumer (DTC) executives relegate their digital footprint to a mere reputation metric, they mistake active pipeline development for simple cost management.

In reality, in a highly digitized economy, a brand’s digital footprint must be treated as a high-yield, compounding revenue engine that requires active management. 

The danger of the passive approach becomes obvious when you look at how customers, partners, investors — quite literally anyone and everyone — interact with a brand online. Long before an introductory call or formal proposal, page one of a search engine serves as an automated background check for every prospect, investor and high-caliber candidate. This digital environment dictates whether or not a deal even has a chance to close, a reality supported by critical market dynamics: 

• At the onset: Industry data indicate that 93% of all online experiences begin with a search engine, making page one a brand and/or an executive’s digital front door. 

• The trust hurdle: Buyers strongly favor independent research; 68% of B2B buyers prefer to research online before engaging with a sales representative.  In conversations with mid-market CEOs, I consistently hear about lengthened sales cycles. The root cause isn’t a bad product; it’s that prospects are disqualifying companies, based entirely on unmanaged search results, before the first sales call even happens. 

• The cost of doubt: If that self-directed search surfaces a fragmented or negative narrative, historical complaints or irrelevant noise, high-intent leads quietly exit the sales funnel, directly suppressing conversion rates and inflating customer acquisition costs (CAC). 

Ultimately, treating search presence as a static score to be monitored four times a year allows third parties and fast-moving competitors to control your brand’s narrative. To capture modern demand and protect margins, executive leadership must stop playing defense and start managing search results as the aggressive distribution channel it is meant to be. 

The page-one economy 

Marketing organizations invest significant capital in optimizing downstream assets such as landing pages, automated nurture sequences and sales scripts. However, far less strategic energy goes into controlling the search environment above the click, where consumer trust is actually won or lost. 

Every dollar allocated to paid media or organic campaign traffic is essentially a wager that our search destination will withstand scrutiny. A flawless user interface or an aggressive ad buy cannot overcome a search results page laden with brand inconsistencies or unmanaged risks.  

The actual conversion decision often occurs in the search engine results page (SERP) before a prospect ever navigates further. In fact, search behavior data shows that the first organic result on Google captures 28.5% of all clicks, with click-through rates dropping sharply to just 2.5% by the tenth position. 

Look at your current marketing budget. If you are spending $50,000 a month on Google Ads but ignoring the organic complaints right next to those ads, you are actively subsidizing your own friction. We must stop treating paid acquisition and organic reputation as separate silos. 

If those premium top positions are held by disjointed or negative third-party content, brands and executives lose traffic they have already paid to attract. With this, there is a compounding business advantage. Imagine two businesses execute identical marketing budgets with identical creative assets; the company that actively owns and protects its digital search real estate captures significantly higher conversion rates. Over time, this variance compounds into a financial advantage in customer acquisition and customer lifetime value. 

Transitioning reputation into financial growth 

Historically, companies have regarded online reputation management as a defensive, reactive crisis communications and PR function. In today’s digital reputation landscape, the market leaders who treat their search footprint as an offensive growth asset are the market winners. 

When a brand’s search environment is proactively structured with its digital reputation prioritized, overall marketing performance rises. Paid search performance increases because prospects see cohesive, positive and accurate organic results. Organic traffic converts at higher rates because supporting digital assets validate organizational credibility, and proactively managing this pre-click environment can drive overall revenue while reducing operational acquisition friction. 

Ultimately, safeguarding the digital front door is no longer just an IT or marketing task. In a digital-first economy, controlling the narrative on page one is a core fiduciary responsibility for the modern chief executive. 

Executive summary for leadership 

If your current marketing strategy excludes proactive search and digital reputation management, your team is optimizing only half of the conversion equation. What prospects find in the moments immediately preceding business engagement dictates the financial return on your entire ad spend. 

The goal is not simply to spend more capital, but to spend it strategically through a proactive lens focused on the brand’s positive digital reputation. A strategic, well-curated search results page is not a side project for corporate communications; it is the first consumer impression, a primary trust signal and a critical line item on a brand’s revenue statement. 

Many CEOs treat their company’s online search presence like a quarterly credit score — checking it periodically to ensure no major damage has occurred, then forgetting about it.  

Such a passive and defensive view misses how online searchers actually make decisions today, representing a fundamental misunderstanding of modern enterprise growth. When business-to-business (B2B) or direct-to-consumer (DTC) executives relegate their digital footprint to a mere reputation metric, they mistake active pipeline development for simple cost management.

In reality, in a highly digitized economy, a brand’s digital footprint must be treated as a high-yield, compounding revenue engine that requires active management.