Build AI Apps That ChatGPT Can’t Kill

2025-09-01
Build AI Apps That ChatGPT Can’t Kill

The AI app landscape is moving incredibly fast. Even ChatGPT, the most mainstream of AI apps, is gaining new capabilities every month.

For users, this can be exhausting.
For app developers, it can create a feeling of existential dread.

For your app to survive in this competitive landscape, you need to build a moat on ChatGPT’s weaknesses.

Serving a Niche Audience

Focusing on a niche audience is key. ChatGPT is a generic tool designed to help the vast majority. Developing AI applications tailored to specific needs ensures you’re addressing gaps not covered by broad solutions like ChatGPT.

Optimized User Interface

While text-based interfaces are convenient, they aren’t the most effective user interface for every task. Creating a user interface that caters to specific tasks can offer users an experience that a generic chat can’t replicate.

Think of interactive graphs for data analysis or drag-and-drop features for project management which add tangible value. When I admin documents, for instance, a visual dashboard is my go-to.

Automation and Integrations

I sometimes find myself burdened with mundane repetitive tasks. Here, applications with automation capabilities (agents) shine. However, ChatGPT does not (yet) adequately fill this space, making automation a significant moat.

Leverage workflows and seamless integration with tools like Slack or Notion. Remember, Model Context Protocol (MCP) will allow ChatGPT to operate tools, yet custom automation tailored to specific user needs can still set your application apart.

Privacy

In developing AI applications, adhering to privacy standards such as GDPR is non-negotiable. Giving users confidence in their data safety is crucial. Using local AI or locally-hosted cloud solutions (such as Berget AI for Sweden) can be the answer.

Multi-user

ChatGPT is designed as a single-user experience. Incorporating multi-user capabilities elevates sharing and collaboration—transforming applications from solo utilities to vital team assets.

Trust and Brand

In a world where anyone can spin up an AI app overnight, who is behind the product matters as much as what it does. Users and companies want to know the service is reliable, transparent, and built by people with authority in the field.

A strong brand, thought leadership, deep insights about your topic area, and clear communication about ownership and responsibility create confidence. Trust becomes a moat: if people believe in you, they’ll pick your product over a faceless chat app.

Summary

In summary, the path to resistant AI applications lies in:

  • Own your niche: Focus on a specific audience or use case where a generic chatbot feels shallow.
  • The right user interface: Go beyond chat. Build UIs for complex tasks where interactive interfaces, forms, dashboards, or visualizations beat plain text.
  • Leverage unique knowledge: Embed proprietary context, domain expertise, and internal documents that ChatGPT doesn’t have access to.
  • Collaboration: Add multi-user features like shared workspaces, comments, and roles that turn your app into a team tool.
  • Privacy & compliance: Solve for privacy, GDPR, and industry-specific regulations that enterprises can’t ignore.
  • Automate workflows: Extend from “answers” to “actions.” Trigger tasks, connect APIs, and orchestrate processes. (Yes, ChatGPT Agents are coming: but you can specialize faster.)
  • Integrate deeply: Plug into the tools your users already live in: Office, Slack, Notion, Figma, CRMs. (MCP will reduce this moat over time, so lean on tight, opinionated integrations.)
  • Trust and Brand: Users choose products with a credible source.

These strategic moves ensure your AI can operate in spaces even the mighty ChatGPT cannot fully reach.