The whiteboards in the lobby of practically every venture capital firm in San Francisco today tell an odd tale. Marketplaces, mobile apps, and subscription businesses were all covered by startup diagrams ten years ago. The diagrams now have a different appearance. There are “model” boxes, “agent” arrows, and very few people in the flow.
Technology giants were businesses for the majority of the internet era. Search was created by Google. E-commerce was run by Amazon. Apple created software ecosystems and devices. Every morning, armies of engineers, marketing teams, payroll departments, and headquarters entered glass buildings.
| Category | Details |
|---|---|
| Concept | AI Model as an Economic Platform |
| Current AI Leaders | OpenAI, Google DeepMind, Anthropic, xAI |
| Key Technology | Large Language Models and “World Models” |
| Emerging Trend | AI Agents performing autonomous tasks |
| Economic Shift | From Software-as-a-Service to “Services-as-Software” |
| Potential Capability | Autonomous planning, negotiation, coding, decision-making |
| Industry Direction | AI assistants embedded in operating systems and digital ecosystems |
| Example Use Cases | Automated coding, legal research, financial analysis |
| Emerging Term | Agentic Economy |
| Reference Source | https://fortune.com |
However, there is a growing suspicion in Silicon Valley that the next big thing might not actually look like that. It could be a model. An AI system that subtly becomes the interface through which everything else functions, rather than a software company.
If you spend some time in the AI labs right now, you’ll find that the atmosphere is similar to the early days of the web, with equal parts disbelief and ambition. Engineers train models that increasingly act more like decision-makers than tools while seated behind numerous monitors that glow with code.
While their human supervisors sleep, some of these systems can already write thousands of lines of software in a single night, testing and correcting their own code. It’s difficult to ignore the uneasiness in the room when watching a demonstration of this type of workflow. These days, the software does more than just help. It’s finishing all of the tasks.
And once a system can plan, reason, and execute work, the traditional structure of a tech company starts to look… inefficient.
Tech companies used a predictable model for decades. Software platforms were used by humans to carry out tasks like document writing, data analysis, and product design. We are currently inverting that model. The tasks are starting to be completed by the software itself.
This change is referred to by some investors as the “agentic economy.” AI agents finish tasks on their own rather than using Software-as-a-Service tools to assist employees. coding assignments. legal investigation. analysis of the market. even discussions between businesses.
The business offering services might not be the most valuable entity in that setting. They are being orchestrated by the AI model.
This future is already hinted at in commonplace tech products. Meetings are scheduled by voice assistants. AI programs create emails. Production software that previously required junior developers is written by coding models. The distinction between operator and assistant is becoming increasingly hazy. Investors appear to think that this trend is picking up speed.
Billions of dollars have been invested in AI labs in recent months to create what researchers refer to as “world models”—systems trained not only on text but also on video, simulations, and real-world physics. The objective is lofty: an AI that can comprehend environments similarly to humans, forecast results, create plans, and even communicate with both digital and physical systems.
In an effort to achieve this, businesses like Google, Meta, and Elon Musk’s xAI are investing heavily in computing infrastructure and hiring researchers. Some venture capitalists claim in private talks that the winning model could dominate significant chunks of the digital economy. Not through business ownership. by planning them.
Imagine an AI assistant that takes over as the standard online interface. It automatically communicates with thousands of services, writes software, negotiates prices, plans travel, and manages investments. People just ask the model to do tasks instead of navigating dozens of apps or websites.
At that point, the entry point to the digital economy is essentially controlled by whoever controls the model.
It resembles search engines from the early 2000s. Google quietly gained enormous influence over the internet when it emerged as the primary source of information. That concept could be greatly advanced by an AI super-agent. Skepticism persists, though.
AI models are still costly to train and occasionally unpredictable. Hallucinations continue to occur. Even the most sophisticated systems are capable of producing confident nonsense or stumbling over basic logic problems. Whether they can consistently handle large-scale decision-making in the real world is still up for debate. The issue of power is another.
Despite its flaws, a traditional tech giant has shareholders, executives, and public accountability. Influence would be concentrated very differently under a dominant AI model. The small team of researchers and infrastructure providers who are in charge of the system may hold the true power.
There’s an odd sense of déjà vu as you watch this happen. The tech giant has previously been reimagined by Silicon Valley. Microsoft was founded on personal computers. Apple’s modern empire was built on smartphones. Meta was elevated by social networks.
Every time, the interface was altered, and the new power center was the owner of that interface. Perhaps the AI model will be the next interface.
And if that occurs, the most significant “company” of the upcoming ten years might not even have a campus, a product line, or a well-known brand. Maybe it’s just the system that everyone uses to get answers. That idea still sounds slightly absurd. However, in 1998, search engines also did.
