Inspired by standalone sites like bankstatementconverter.com, a major opportunity in the ChatGPT store is building apps that solve highly specific, painful business problems. An app that automatically finds all K1 tax forms in a user's Gmail is a prime example of a simple tool with massive value for a specific audience.

A professional with a non-technical background used "vibe coding" (low/no-code AI development) to instantly build highly personalized apps for her own life. These included a house-shopping comparison tool based on her specific trade-offs and a custom meal planner for a friend's diet, showing a new level of personal software creation.

AI will democratize software development to the point where building your own custom apps becomes commonplace. Instead of settling for one-size-fits-all solutions, people will create "personal software" perfectly tailored to their specific workflows, like a custom workout tracker.

Tim McLear used AI coding assistants to build custom apps for niche workflows, like partial document transcription and field research photo logging. He emphasizes that "no one was going to make me this app." The ability for non-specialists to quickly create such hyper-specific internal tools is a key, empowering benefit of AI-assisted development.

The barrier to creating software is collapsing. Non-coders can now build sophisticated, personalized applications for specific workflows in under an hour. This points to a future where individuals and teams create their own disposable, custom tools, replacing subscriptions to numerous niche SaaS products.

Individuals will use AI to build bespoke software for personal use. A subset of these tools will find a niche market, creating entrepreneurs who operate outside the VC-funded, subscription-SaaS model, potentially favoring one-time purchase models due to low development costs.

The surprising success of Dia's custom "Skills" feature revealed a huge user demand for personalized tools. This suggests a key value of AI is enabling non-technical users to build "handmade software" for their specific, just-in-time needs, moving beyond one-size-fits-all applications.

Don't start with a broad market. Instead, find a niche group with a strong identity (e.g., collectors, churchgoers) that has a recurring, high-stakes problem needing an urgent solution. AI is particularly effective at solving these 'nerve' problems.

Non-technical users are leveraging agents like Moltbot to build their own hyper-personalized software. By simply describing a problem in natural language, they can create internal tools that perfectly solve their needs, eliminating the need to subscribe to many single-purpose SaaS applications.