Hardware will drive a new type of connectivity

Editor’s note: This perspective comes from an executive leader from a global agency. We were intrigued by the way Michael connected hardware developments to business strategy which ultimately leads to a new kind of user-experience. His vision for a contextual connectivity between devices aligns with another conversation we overheard about Internet 2025. We think this theme deserves some more attention, so stay tuned for an update.

This post was written by human Michael Olaye and narrated by AI Michael Olaye (powered by Wondercraft.ai).

The next internet is going to run on a shared technology stack that is going to fundamentally change the business model of the major platforms. This shift is going to reverberate across the entire internet and redefine what it means to be connected and online. Pay attention to this shift because if you work, play, and exist anywhere on the internet, you will feel this.

This post will focus on two things: 1) I will describe what is happening now, so I can 2) predict (and promote) a new kind of internet.

The best way to understand the incoming changes is to understand the outgoing model: we are in the waning days of the siloed internet. In this system, the platforms have already built up their own massive proprietary system that profit out of their exclusivity. The entire system is designed to have very little overlap from one platform to the next. 

Apple has a reputation for strong silos. Its rivalry with Google is a good example of this. The overlaps between the two platforms are limited, quarrelsome, and exist to underscore brand distinctions across identical service offerings. Until recently, iPhone users were prevented from making Google Maps the default navigation app; and Android users continue to be outed in group chats by notorious green text bubbles. Notice, though, that the nature of the relationship changes when the two platforms have complimentary services.

It has recently been revealed that Google has paid Apple billions of dollars to be the default search in Safari. It is important to break this down: Apple has no stand-alone search product. As a result, Apple synced its billions of consumers that own hardware (the iPhone) and its software (Safari) with Google’s proprietary software (search).

This deal is a preview of a new business model that will transform Silicon Valley platforms from competitors into collaborators. AI is already starting to do it.

The next internet is accelerating too fast for competition to exist in conventional ways. The innovation curve of AI, combined with Nvidia’s hardware stack is forcing platforms to change their business strategy. Nearly every month, the exponential advancement of AI models and GPUs reinforces the same core point: no one will be able to catch up to this, not even the platforms.

The platforms are now realizing that all the cash in the world is not going to buy them enough time to get ahead of the perpetual innovation curve of the next internet. If Apple dedicated its resources to developing a proprietary LLM, it would take years to build and deploy, and get lapped by another competing model within 12 months. Time is the first issue. The second issue is hardware.

Since the emergence of AI transformers in 2017, we’ve witnessed machines developing progress autonomously, shifting the focus from user access to hardware access. This dynamic sets the stage for unconventional relationships between big tech social/data companies and hardware technology giants. This is where Nvidia’s central role in the new foundation for the web is going to architect a new layer of connectivity.

This is not an arbitrary theory for business strategists; the implications of these changes will redefine the way every individual uses the internet. Every time I turn on my smart TV, I have to perform a sequence of rudimentary actions that essentially identify myself for my device. Think of those actions as accessing and connecting the silos across all the various networks, services, and devices.

Let me start with the obvious point: I expect the next internet to know who I am before I jump on it. Additionally, I expect more context clues to be drawn from my behaviors and moments that will enable deeper physical/digital interactions. Who else is in the room with me when I turn on the TV? What do they bring to the moment that alters the experience? 

Imagine having a personal AI assistant that accesses and compiles personal open graph data from both online and offline sources. These data sets, available through business partnerships, power AI, autonomous, and robotic products—all linked by a single AI persona representing your interests. It sounds far-fetched, doesn’t it? This system reminds me of J.A.R.V.I.S.

The next internet is going to turn the moments of our life into the main show.

On a typical day, this AI seamlessly transitions across different products, maintaining context—from your morning routine to meal preferences to home preparation—all without constant human input. While elements of this scenario exist today, they often operate in isolation, requiring ongoing context from users. Who wants to tell their Google Home to adjust the heating when they’re already hot? My AI would know better.

The UI of the next internet will be largely invisible; prompts will come from a combination of implicit and explicit user actions – like the difference between a behavior as a prompt and a command. The brands and platforms that power these connections will recede into the background a little bit more. In this way, the platforms will mirror the networks of the television era; they have a vibe, broadcast their content, but at the end of the day, the main show is all that matters.

The next internet is going to turn the moments of our life into the main show; our online experiences will be more connected, more contextual, and more personal.

Editor’s note: Internet 2025 became the perfect context for our Co-Founder to unveil a list of internet terminology he has been keeping in secret for many years. He has been quietly adding to this document since a conversation about Webmasters dragged on in the year 2007. We expect to add more items as we continue with this issue. Let us know if we are missing anything by writing here.

Editor’s note: This perspective comes from a consulting leader who deals exclusively in business & tech innovation. As Saneel puts it, the traditional sources of digital disruption are being upended to favor the incumbents. These platforms will be shaping the way generative AI bends a variety of consumer-facing industries into personalized marketplaces.

This post was written by human Saneel Radia and narrated by AI Saneel Radia (powered by Wondercraft.ai).

Amidst all of the noise surrounding the emerging disruptive power of AI – and generative AI in particular – one crucial point seems overlooked and possibly even misunderstood. That’s the fact that AI could be the first technology revolution that better serves the large incumbents and established players than it does the startups looking to disrupt them.

This time, it’s

different

The model for disruptive innovation, originally coined by Clayton Christensen in his seminal book, The Innovator’s Dilemma, has stood the test of time surprisingly well. As Christensen puts it, when disruptive technologies arrive, entire industries change and the lines between them blur. Incumbents are slow to respond because they find it difficult to prioritize the new dynamics over their more sustaining innovation efforts. They start to fall behind to a new set of competition they didn’t recognize to be a threat initially. Over time, these former category leaders are relegated to niche, often premium offerings as the mass market value equation has changed forever. This has proven true repeatedly in categories as diverse as newspapers (the web), cameras (mobile phones), railroads (automobiles), healthcare (retail clinics), and music (streaming).

The pace of that change has only continued to increase based on a view of the most important innovations. This familiar disruptor narrative usually includes an upstart with limited resources beginning in a garage and going on to become a behemoth of a competitor thanks to opportunities afforded to small players believing in the potential of these technologies. Today’s largest technology companies by market cap have been the beneficiaries of riding these disruptive waves, such as Amazon, Google, Meta, and Netflix.

As we sit now in the early days of the AI revolution, the conventional wisdom states that this set of disruptive technologies will bring more of the same. Small companies we’ve never heard of will begin to replace today’s old guard of incumbents who are too slow to learn about them, adopt them, and optimize for them. However, a closer look at the facets of AI implies a different future than the cycle of disruptive innovation we’ve grown accustomed to. This is largely because the resources needed to benefit from AI, and the still emerging opportunities to apply generative AI, are where large players across categories have distinct advantages.

Advantage 1

AI thrives on the data

incumbents

have in droves

Let’s start with a simple truth: Data is the critical factor that yields compound returns on what AI can do for an organization. The large AI providers know just how critical the right data sets are for the clients they serve and have focused their efforts on these players by mixing public and proprietary data sources. Consider IBM’s Watson AI for agriculture, advising farmers on planting strategies based on weather data (public) and soil conditions (private); it’s explicitly built for the large agricultural complex, not the independent farmers dotting various national countrysides, because that’s where the private data scales and makes the entire system smarter over time.

Of course, large organizations still have to build the appropriate infrastructure to leverage their data so it is centralized, accessible and updated for evolving use cases. But after years of digital transformation, cloud migrations, and readily available off-the-shelf solutions, many have achieved this in some capacity. Companies like Coca-Cola and BMW have started to reap the benefits of applying AI across their supply chains, production quality control, and in (some) personalized marketing and CRM efforts. This existing infrastructure can now be used to develop native AI offerings and customer experiences with huge benefits. Data has always been a super power for companies that own it and succeed at data organization. It’s no coincidence that the world’s largest companies also happen to be the most data-rich. This wave of disruptive innovation is not happening in a garage; it’s happening in the cloud. The companies leading the way are not no-name startups that lurk in the shadows; the companies dominating the AI space are household names that are already data- and cash-rich, such as Microsoft, Nvidia, Alphabet, and Amazon. They each have intensified their focus on AI, channeling significant resources into this area, marking a strategic shift in recognizing AI as central to future product innovations and the next wave of industry development.

Companies like Coca-Cola and BMW have started to reap the benefits of applying AI across their supply chains, production quality control, and in (some) personalized marketing and CRM efforts. This existing infrastructure can now be used to develop native AI offerings and customer experiences with huge benefits.

True, these digital platform companies will be armed to compete in even more spaces, but it’s also good news for any large company, regardless of industry. For those non-digitally native corporations with complex, regulated data sets such as those in Financial Services, Healthcare, or Mobility, the power of the data they hold serves to create an even larger moat for rising challengers to cross as they consider AI offerings – either as software or services. Huge tech players see the potential to service companies in any category and help them unlock the power of their data. A prime example is happening at JPMorgan Chase, where their extensive, proprietary data enables superior performance in AI-driven financial analysis and risk management. This vast reservoir of data allows them to achieve deeper insights and more robust risk mitigation strategies, a clear competitive edge over startups that must rely on limited proprietary data or the public resources available to any competitor in the category.

This is further advanced by the fact that, as noted above, the players offering them AI services also happen to be those for whom they’ve previously turned to for cloud services and broader IT infrastructure. Cloud technologies helped leaders become more agile, and likewise, AI offerings from the same vendors has the potential to accelerate transformation for incumbents who can leverage the vast data they already possess. The broader that data set and the more proprietary it is in nature, the greater the returns will be, turning what used to be the slowing and rigid infrastructure of being a big company into a set of unique advantages against smaller companies. It’s exactly why tech companies are quickly building services to help these large entities and are growing them more robust daily, such as Amazon’s Bedrock, IBM’s WatsonX, and Dell Technologies Project Helix. There are parallels to how ecommerce capabilities unfolded with shopping tools being built on core platforms big entities had previously licensed, enabling customization, visualization and other unique shopping features for those with the inventory and production capability to service emerging customer behaviors.

The value of proprietary data on centralized infrastructure is an advantage that will grow quickly in the coming year. The current magic of AI infrastructure providers like OpenAI (the creator of ChatGPT) is built on the back of publicly available data, which will only make the power of proprietary data more powerful as more and more players start to harness its power. Arguably, the benefit of proprietary data will grow even bigger as legal challenges and more regulatory scrutiny about the use of the data they’ve ingested (see the New York Time’s recent lawsuit against OpenAI over ingesting decades of their published content).

Advantage 2

Connecting the dots exponentially improves with

more dots

As we look specifically at generative AI, the story only gets better for organizations that have invested deeply to build customer relationships across multiple channels. In previous eras, incumbents would find it difficult to compete with startups that win customers with “just good enough” offerings (at dramatically lower prices), or by focusing on the one true driving force of innovation the past few decades: convenience.

Yet generative AI’s greatest potential lies in its ability to personalize at scale. Marketers at organizations of all sizes have been the first to dive into leveraging AI because targeted personalization has always been the holy grail of customer acquisition and experience. Each and every touch point with a customer is an opportunity to personalize, and the ability to tie those experiences together across channels is the level of convenience and service customers look for in the vast majority of industries, both in B2B and B2C. Any large company has more touch points to offer their customers than their smaller, emerging competitors, and now those have the potential to adapt seamlessly at an individualized level thanks to Generative AI.

When you couple this highly personalized future with the power of top-line AI – that is the ability to integrate a number of offerings into a single customer experience from trip planning to healthcare to wealth management – you can start to see why incumbents have yet another opportunity to win. Vanguard’s AI-powered robo-advisors offer personalized investment strategies to cater to diverse customer needs. These can only feel personalized where there is enough optionality to even offer in the first place. The more an organization has to offer via their own products or services or even via that of their global partnerships (another arena large companies tend to excel), the more they benefit by being a single destination for customers. Where before rigid brand architectures and “product search” challenges could result in customer confusion, generative AI can seamlessly weave all these offerings together to ensure customers get exactly what they want, when they want, and importantly, how they want it.

Advantage 3

Pricing power

drives long-term returns

Finally, one topic that is far too often ignored as it relates to the forthcoming AI revolution is the role of pricing. In previous eras, especially our venture capital driven recent past, young companies had incredible resources before they had even proven themselves, and new competitors could afford to undercut on price while incumbents dealing with margin demands struggled to maintain market share. In a world of personalized commerce and experiences, the size of a company can much more effectively drive its pricing power. The broader the ecosystem of offerings and the clearer the view into life-time customer value (viewable with the right data), the more flexible a market leader can be in what it charges, when, and to whom.

This applies beyond just promotional cycles. Dynamic pricing is on the rise and has been a game changer for insurers and mobility companies, but with AI the barriers to test and learn down to very specific audiences is unprecedented. Uber has leveraged dynamic pricing for years because it has a clear view of supply and demand. Now imagine how that evolves in any category for companies that know exactly how much they can sell and over what time period to new or existing customers. As noted above, startups are often single product companies (something Instagram has been a uniquely prolific creator of), while large companies with portfolios of offerings that are diversified across goods and services have many more variables they can leverage to make real-time pricing decisions to maximize lifetime value, not just secure immediate transactions.

Companies with diverse offerings can view and respond to each customer in a wholly personalized way that looks at the bigger picture of the value they bring.

Of course, that doesn’t mean large incumbents won’t continue to feel pricing pressure from upstarts, but it does mean they will have more control than ever on which customers they want to invest in, and which may actually be best left to attrition.

Accelerating this change is the fact that traditional loyalty programs are giving way to what could arguably be called membership models. This trend will only dramatically increase as AI becomes more commonplace in pricing decisions. Companies with diverse offerings can view and respond to each customer in a wholly personalized way that looks at the bigger picture of the value they bring depending on their understanding of how consumers access various parts of their portfolios, and those that are functionally integrated (vs. horizontally or vertically) will have unlocked a new superpower via AI. Where The Innovator’s Dilemma is really just the difficulty of prioritizing tomorrow over today for a mature company, generative AI has the potential to evolve relationships with the real-time pricing models to manage for both effectively.

Innovation,

without the garage

We all expect AI to be revolutionary across the economy, and the earliest signs are already here for any organization that has even experimented with the technologies. What’s different about this revolution is that existing data infrastructure, partnerships, and customer relationships are actually the very tools to best lead the revolution.

For decades, multiple technology revolutions (web, mobile, cloud) have scared incumbents eyeing new forms of competition on every side as they read about the “overnight success” stories emerging from nowhere in their respective industry trades. Yet, the future looks starkly different as the AI revolution takes hold: this next era of disruptive technologies will actually benefit those that are already large and diversified. It’s a revolution where innovation will come less often from a garage, and instead emerge from the board room.

…At least for those companies that understand the unique advantages they have if they dare apply it.

Superformats

Will

Save Media

in the

New Internet

Editor’s note: A new model for media is taking shape right in front of our eyes. What does it look like? That’s where it gets a little complicated. As you can see in this post, the ongoing disruption is real but the way it ultimately shakes out cannot be accurately predicted. Nevertheless, this post lays out a compelling case that media will be revitalized in 2025. Stay tuned for more follow ups on this front.

This post was written by a human and narrated by an AI-generated voice. (powered by Wondercraft.ai).

The ad-sponsored media model is dying. Good riddance. This system propagated the worst traits of an inefficient (and dumb) economic model: placing annoying ads on top of unnecessary articles to chase after search traffic. It is hard to imagine a more self-destructive system. A new model is emerging, but the specifics of it are not yet clear.

Substack Started It

Substack sparked a half-step towards a new model. It demonstrated that individual creator voices delivering quality content can drive revenue, but not necessarily scale. The key building block of this success was the direct relationship between creators and audiences. The surge of newsletter subscriptions hinted at a long festering demand.

Content alone will not sustain subscription revenue, nor can it really define the underlying relationship.

The key problem to overcome, however, was the content. Content alone will not sustain subscription revenue, nor can it really define the underlying relationship. This novel system was a start in search of a next step. Consumers need more direct value and all these creators could offer was another email.

LLMs Will Shape It

The next step came with the rise of LLMs and other generative systems. These systems convert bytes to bits and repackage them into customized, personalized experiences. Now the creator/audience relationship has a jolt of relevance. The traditional content formats – the articles, emails, podcasts, etc – that contain all of the context and information are now able to be collected, recalled, and repurposed to fulfill multiple consumer needs. On top of that, the delivery mechanism is now centered around context-rich moments. Rather than passively receiving emails, these systems respond to consumer prompts.

Introducing Superformats

I am calling this real-time development of personalized content packages the “superformat.” This system can translate and execute differing consumer signals into a more direct value-exchange. Consumer signals that hint at buying can be met with CTAs to purchase (with affiliate deals). Signals to learn more can drive to lean back consumption (with relevant sponsorships). And following developing stories can result in predictable consumption habits that are valuable for brands.

If the traditional article page is a glass, the superformat is the water in it. Internet 2025 is when the glass breaks and the water spills out.

One thing you will notice about a superformat is that it is deliberately amorphous. It is the anti-snowfall, in the sense that its shape and production are determined by the context of the user, not the requirements of the advertiser, publisher, or even the product designer. It is easier to understand the essence of a superformat than it is to imagine what one looks like. If the traditional article page is a glass, the superformat is the water in it. Internet 2025 is when the glass breaks and the water spills out.

A New Kind of Media Model

Once you accept the atomization of content, the rest is easier to follow. The old order that held things together in silos can no longer hold. My vision for this new system is still taking shape so I can only paint a generalized picture: individual creator voices will partner and merge their audiences in decentralized touchpoints. They will organize more around psychographic traits than topic verticals or geographic locations. The makeup of these businesses will look different than conventional publications, but stories and storytelling will still be the essential lubricant that keeps the value flowing for all parties.

Once you accept the atomization of content, the rest is easier to follow.

The change that is coming is going to be big, but that does not call for doomerism or pessimism. There is a habit to over-interpret sensational stories about AI disrupting industries and jobs. The market is still open to those that are willing to adapt and to more closely connect with the needs of their audiences. Throw away the conventions and just deliver the goods.

Presence is the

Next Frontier

in Connectivity

Editors Note: What if Internet 2025 was really a story about enhanced digital infrastructure? The majority of the future-speculation focuses on novel consumer tech experiences but pays little attention to reimagining the way devices connect. This perspective comes from a technology executive who has a compelling vision for how humans and devices will soon interoperate.

This post was written by a human and narrated by an AI-generated voice. (powered by Wondercraft.ai).

Since 2019, the number of connected devices inside homes has increased 40%

The New Internet Will Look Very Familiar

Editor’s note: We’ve heard – and promoted – our fair share of sensational takes about the next internet, so it is with a special sense of duty that we offer this push-back. This perspective comes from a technology executive who was very interested in splashing cold water on the revolutionary framing of the future internet. Stay tuned for a counter-take.

The Internet

What I would

Kiss

The features, apps, and conventions that briefly infatuate us. They seem so wonderful at first, but something about them fails to deliver.

Notifications

God they were amazing at first, but now it’s insane. They are interrupting everything in our lives and totally not worth it. — AI entrepreneur

DAOs

Idealistically what it represents is something that something that is built around a set of core values, shared values. People join and are a part of something because they all they all have something in common.

Search

Being able to search, I think it’s so powerful, but the format of this experience is not right. The way it works now is you enter this search term and get these 12 links which forces you to refine that search with 12 more links, right? I would want to get rid of that and have it be a more natural, predictive way of talking and searching. — Brand Executive

Flash

It was so fun and sexy and I miss it. — CEO

Algorithms

Algorithmic sharing of content. We sorted it and we’ve reached its logical extreme and it was a good run. We’re great at it; we dominated; we won. By winning, we lost. We lost because, literally, what will get shared is what will what will suck you in which is low quality content whenever you need it. — CEO

Outbrain

It sucked and was stupid, but it could have been amazing. — Brand Executive

What I would

Marry

The long-term opportunities and features that showcase the best of what the internet can offer end-users, brands, and platforms. This is way bigger than infatuation; this is love.

Online Gaming

I think gaming will combine movies and storytelling – big narration – that is going to be really interesting. Then you can actually kind of be a part of it. And with that comes all that personalization that creates your flavor of that. It’s going to be huge. — AI entrepreneur

LinkedIn

As a productivity tool that supports what we do at a professional level, I think it’s phenomenal. And a social network that seems to have maintained a level of positivity that doesn’t exist elsewhere. — Famous podcaster

Spatial Computing

I believe it’s in it for the long term. It’s not just flashy and sexy right now, though it is. But it will be transformative and here for a long time and continue to evolve and get better like any good marriage. — CEO

Blockchain

We are selling it wrong; this is not meant to be a front-end benefit. No one needs to know what’s even there. But I think it will underpin the next internet. I’m thinking about the fediverse side stuff and the decentralization of our social networks for example, or being able to move your identity wherever you want. I get so excited by tokens and authenticity. — Brand executive

Blockchain (again)

It is the most boring thing I could possibly say. But I actually do believe that blockchain as an identity-based solution will change the way we use the internet forever. — CMO

Home Pages

They are still one of the most overlooked pieces of the internet. Don’t sleep on the value of a really good home page, no matter what everyone tells you about side door entries. — Brand Executvie

What I would

Kill

Do we need to explain this one any further?

iMessage

Two reasons: one, monopolistic dominance over any other potential competing products; and two, because the user experience just fucking sucks, and a company with $400 billion in cash on hand that cannot in any way innovate around making something that they have a non monopoly over better is very risky. This is one of the most frustrating things about Apple to me and I love that company. — Founder

SmartPhones

iPhone neck and other issues with this stupid screen we keep in front of our faces like that. — Founder

SmartPhones (again)

Its days are numbered so I’m just getting it over with. — CEO

Social Media

I would kill it in the way that it represents a fake life. Yep. Right. So this whole story of ‘I’m living my best life and everyone is living a better life than me.’ Right? I would kill that party. — Brand executive

Fortnight

They are creating unchecked environments for minors and kids to engage in behaviors that are resulting in mental health and socially unhealthy behaviors and actions. — CMO 

Ad-Funded Content

I think that the main problem with the internet today is that it’s fully advertising-funded, right? With only a few exceptions. And the problem with advertising-funded means that we don’t give a fuck about the quality of the content. — CEO

The Future of Media is Personal

A lot more content is coming

Overheard at ON_Discourse

From the editor: Is digital media doomed? The following perspective comes from a guest who was an executive at one of the biggest newsrooms in the world. It builds off another point we overheard about how news should be thought of as a service, not a product. This kind of thinking can transform news consumption into a personalized experience.

I pay for ESPN+. This subscription gets me access to countless streams that have no value to me at all. The only reason I pay is to access my team’s games. Are you telling me this kind of subscription model is a good thing? We are on the brink of a new kind of subscriber relationship that will be powered by AI and proprietary data.

We have to stop thinking about AI as if it is a replacement technology. AI is the ultimate enabler.

The first point is about the data. I have been paying ESPN directly for six years. They have collected data on my team & league affinities, watching preferences, and triggers. This data is not big enough to launch an ESPN LLM, but that does not matter; there are other ways to integrate smaller sets of proprietary data into another platform’s LLM. The bottom line is that ESPN can finally have access to the enabling technology that can ultimately deliver a true personalized experience. I don’t think we know yet how amazing this experience will be. It is going to be worth the money.

We have to stop thinking about AI as if it is a replacement technology. AI is the ultimate enabler. Media brands need to embrace the way this tech can foster novel content experiences. Doing so will revolutionize the relationships audiences have with their media brands. I am typically a pessimist when I think about the future of the internet, but this scenario gets me legitimately inspired.