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Following the initial buzz, the AI Agent market evolved through several stages:

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Phase 1: Experimental Phase

  • Experimentation: Projects focused on what AI Agents could do, from simple bots to more complex interactive entities.
  • Lack of Structure: Initially, there was little in terms of standardized functionalities or revenue models.

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Phase 2: Commercialization

  • Business Models: Monetization strategies began to form, with AI Agents being used for marketing, community building, and even direct revenue generation through services or content.
  • Platform Development: Platforms like aiPump emerged, providing tools to create and manage AI Agents, making the technology accessible to more than just tech experts.

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Phase 3: Maturation

  • Utility Driven: The focus shifted towards creating value through utility, with AI Agents taking roles in:
    • DeFi
    • Gaming
    • Education
    • Streaming and entertainment
  • Regulatory Attention: As the market grew, so did interest from regulatory bodies, leading to a push for more transparent and compliant AI Agent operations.
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