LLM-Driven Apps: A Revolution in Replacing Traditional Software and OS Features

I continue the AI future LLM series, this article no 4, previous article The Future of LLM-Driven Apps: Redefining User Interaction | LinkedIn

We talked about the LLM-driven apps, they are replacing traditional apps including enhancing core operating system features.

But this raises critical questions: How far will this trend go? Are we heading toward a world where more apps and OS features are replaced entirely by LLM-driven solutions? And how do we ensure these tools remain adaptable to specific user needs?

LLM-driven apps are redefining software and OS design, consolidating features and workflows into seamless conversational interfaces. But the next step is clear: Apps Language Model (ALM). By tailoring AI to specific apps, ALM ensures that users get not only the power of LLMs but also the personalization and adaptability they need.

This article explores the growing influence of LLM-driven apps and sets the stage for the next evolution: the concept of Apps Language Model (ALM)—a tailored solution that bridges the gap between consolidation and personalization.

In the next article of the Future AI LLM series, we’ll explore how ALMs will revolutionize app development and user experience, taking LLM-driven apps to the next level.

1. The Trend of Consolidation

LLM-driven apps are disrupting the software ecosystem by consolidating functionalities traditionally spread across multiple apps or OS features.

Instead of relying on several tools, users now turn to one conversational interface to handle tasks like:

• Grammar checking and content creation.
• Media design and brainstorming.
• File search and contextual problem-solving.

This trend simplifies workflows but also challenges developers and businesses to rethink the value of standalone apps.

2. Apps Already Replaced or Disrupted by LLMs

Many apps are already being replaced or disrupted by LLM-driven tools.

Here’s a breakdown example:

3. OS Features Enhanced or Replaced by LLMs

Operating systems have traditionally been the gateway between users and software.

LLMs are disrupting this relationship by embedding conversational AI into OS-level workflows.

Those some examples, i would say we might think building operating system based on LLM .... sound scary!!!

4. The Challenge: Generic LLMs vs. Specific Needs

While the trend of consolidation is powerful, it has limitations:

• Generic LLMs: Broad in scope but lack the specificity required for app- or task-focused workflows. Can feel overwhelming for users who need tailored, app-specific interactions.
• Need for Personalization: As users rely more on LLM-driven apps, they demand tools that adapt to their unique workflows and preferences.

This is where the concept of Apps Language Model (ALM) comes into play.

Keep tuned for next article to cover the Apps Language model