How GPTs Became the New Apps

How GPTs Became the New Apps

How GPTs Became the New Apps

The smartphone era gave us app stores, icons, and swiping gestures. But make no mistake: a new paradigm is rising — GPTs as the next app layer, where conversational agents become the default surface for computing.

The end of screens as the interface

Back in 2007, Steve Jobs reimagined how we engage with computers—not by typing commands, but with icons, taps, and scrolls. Now we’re on the verge of the next shift: saying rather than clicking.

OpenAI’s recent rollout of its “agentic” ChatGPT confirms this direction. You can now tell ChatGPT, “Plan my meetings, buy ingredients, and draft a slide deck,” and it can juggle tasks, navigate web tools, invoke APIs, and return polished results. (OpenAI)

In other words, we’re moving from “apps + UIs” to “agents + prompts.”

What makes a GPT more than a glorified chatbot?

Not all conversational interfaces are equal. What distinguishes a true GPT-as-app is its embedded workflow, context, and data integration:

  • Prompt engineering + domain specificity

  • Access to your tools, data, APIs

  • Memory and session continuity

  • Safety, verification, constraint logic

As one architect put it:

“Agents are not only going to change how everyone interacts with computers. They’re also going to upend the software industry, bringing about the biggest revolution in computing since we went from typing commands to tapping on icons.” (Applied AI Tools)

Bill Gates has similarly predicted that agents will shift computing toward intention and away from interface friction. (Applied AI Tools)

Why now is the inflection point

Three converging trends make this possible:

  1. Model sophistication — GPT-4 and successors are capable of context, chaining, reasoning, and tool use.

  2. Interoperable systems — APIs and data plumbing let GPTs become “apps with backends.”

  3. User adoption of conversation — People already talk to ChatGPT, Siri, Alexa; they're getting comfortable with “just ask.”

In fact, analysts are already forecasting that 2025 will be the year AI agents infiltrate enterprise workflows, “materially chang[ing] the output of companies.” (Inc.com)

A Forbes headline put it bluntly:

“Why AI Agents — Not ChatGPT — Will Dominate 2025.” (Forbes)

The upside (and danger) of appless apps

For product teams, this is a once-in-a-generation shift:

  • Feature creation largely becomes prompt + plumbing, not full pages of UI code

  • Launch cycles collapse

  • Value accrues to who owns the prompt/agent architecture, embedding logic, and data connectors

For investors, this yields modular verticals: you don’t need Facebook-level scale; you need defensible GPTs in targeted domains (law, property, healthcare, identity). But the big risk is commodity overlap — dozens of GPTs doing the same thing. The defensibility lies in proprietary data, integration moats, or domain regulations.

The dark side: hallucinations, drift, duplication

Language models are fragile. Without rigorous guardrails, GPTs can hallucinate, misinterpret, or behave unpredictably. Many early GPTs rehash similar prompts, leading to saturated overlap. An academic survey found that early GPT apps proliferated but plateaued in new creativity. (Medium)

The analogy is telling: early mobile UX was chaotic until app stores, design guidelines, and norms emerged. We’re in the UX wild west of GPTs.

Looking ahead: the agent economy

Apps once abstracted hardware. GPTs will abstract menus. In the next decade, your “app” might just be a prompt and context.

So the question for any founder, product leader, or investor is no longer which mobile app, but what agent — and whether it has the data, logic, and safeguards to survive commoditization.

 

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