In the early 2000s, Agile development emerged as a groundbreaking approach to software development, emphasizing adaptability, collaboration, and delivering working software in short iterations. The Agile Manifesto, created by a group of software developers, outlined key principles such as individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a plan.

Agile quickly gained popularity in the tech industry, with many companies adopting it as their preferred methodology for developing software. Its iterative approach allowed for faster delivery of functional software, increased collaboration between team members, and greater flexibility in responding to changing requirements.

However, as technology continues to advance at a rapid pace, Agile's limitations have become more apparent. The need for constant communication and coordination among team members can sometimes impede progress, especially as teams grow larger and more complex. Additionally, the reliance on human intervention for decision-making and problem-solving can lead to bottlenecks and delays.

In response to these challenges, a new trend is emerging in software development: solo-man teams using AI to iterate and build software. By leveraging artificial intelligence and automation, these teams can streamline the development process, reduce the need for constant communication and coordination, and quickly adapt to changing requirements.

While Agile development has been a valuable methodology for many years, its time may be coming to an end as solo-man teams using AI are able to deliver software faster, more efficiently, and with fewer setbacks. The future of software development may indeed lie in the hands of these small, agile teams empowered by artificial intelligence.