You can't directly "game" an AI to recommend your product. The AI learns from public internet data. The best strategy is to build a product so good that developers organically discuss and recommend it online, creating the very data corpus that trains the AI's future suggestions.

User stickiness for AI models is increasingly driven by the 'harness'—the custom prompts, workflows, and integrations built around a specific model. This ecosystem creates high switching costs, even when a competing model offers incrementally better performance.

For ChatGPT, the true sign of durable value is whether users return after three months. This focus on long-term retention dictates product decisions, with the core belief that revenue is a byproduct of solving user problems, not a direct optimization target.

Despite perceptions of LLMs as interchangeable commodities, user behavior shows significant stickiness. This loyalty isn't just about model performance; it's driven by the overall product experience, workflow integrations (like Claude Code), and agentic capabilities, which make users reluctant to switch even with service interruptions.

Instead of trying to be a closed ecosystem, the most valuable AI assistants will build trust by intelligently referring users to the best external app or service for a specific task. This creates a new distribution layer and makes the assistant stronger, not weaker.

In the AI era, product distribution is shifting from Search Engine Optimization (SEO) to "AI Optimization." AI models recommend tools like Supabase not through paid placement but because they offer a superior developer experience, making ease-of-use a primary driver for go-to-market success in an agentic world.

Unlike the failed GPT Store which required users to actively search for apps, the new model contextually surfaces relevant apps based on user prompts. This passive discovery mechanism is a massive opportunity for developers, as users don't need to leave their natural workflow to find and use new tools.

The new frontier is Answer Engine Optimization (AEO), the skill of ensuring your product or content is the primary answer provided by AI agents. As users shift from search engines to AI chats, ranking within AI-generated answers becomes more valuable than traditional link placement.

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.