For PMs struggling to get AI experience at their current job, building a ChatGPT app serves as a powerful portfolio project. The end-to-end process—from prompting an idea to running evals—simulates the full AI product development lifecycle, demonstrating valuable, hands-on skills to potential employers.
A key distribution advantage of ChatGPT Apps is implicit discovery. The model can automatically surface your app in a conversation if it deems it relevant to a user's request, even if the user has never installed or heard of it. This creates a powerful, intent-driven channel for organic user acquisition.
AI prototyping should be viewed as a fundamental skill for modern PMs, not an extra job responsibility. Just like using Figma to communicate design, AI prototyping tools allow PMs to make abstract AI concepts tangible for stakeholders and customers. This accelerates feedback loops and improves alignment on complex product behaviors.
Developing a ChatGPT app involves an iterative evaluation ('eval') process. This is akin to SEO, where you must test and refine your app's metadata and tool descriptions. The goal is to ensure ChatGPT's model correctly interprets user prompts and triggers your app for relevant queries, which is critical for discovery and usability.
The ChatGPT app platform is not yet a public marketplace; only pre-approved launch partners can publish. Developers building an app today are making a strategic, high-risk bet on the future existence and success of an open app store. You can build and test, but you cannot yet reach a public audience.
Large brands like Target are using ChatGPT apps as high-intent lead generators rather than for full-funnel transactions. The app helps users build a shopping cart within the chat interface and then hands them off to the main website to complete the purchase. This reduces integration complexity while capturing high-value users.
ChatGPT Apps are built on the Model Context Protocol (MCP), invented by Anthropic. This means tools built for ChatGPT can theoretically run on other MCP-supporting models like Claude. This creates an opportunity for cross-platform distribution, as you aren't just building for OpenAI's ecosystem but for a growing open standard.
Users originating from an AI source like ChatGPT convert at a 26% higher rate. While the traffic volume is lower than traditional SEO, the intent is much higher because users have already refined their needs through conversation. This makes integrating with AI platforms a highly effective user acquisition channel.
The key opportunity for solo developers building ChatGPT apps lies in collaborative utilities. Instead of creating simple search or display tools, focus on apps like spreadsheets, to-do lists, or whiteboards where ChatGPT can act as an active partner—filling in data, adding formulas, and generating content directly within your app's interface.