Software agents have reached a point where they can perform complex tasks autonomously, thanks to models like Claude Code. This model can execute multi-step processes using tools like bash and file operations, making it adaptable for various applications beyond coding. The key takeaway is that a robust coding agent can function effectively as a general-purpose agent, capable of managing tasks such as organizing files or automating workflows. The Claude Code SDK empowers developers to create applications where user outcomes are defined through prompts rather than traditional coding. The article outlines five core principles for building effective agent-native applications: parity, granularity, composability, emergent capability, and improvement over time. Parity ensures that whatever a user can achieve via a user interface can also be done by the agent using tools. Granularity emphasizes the need for atomic tools, allowing the agent to operate flexibly rather than following a rigid sequence. Composability lets developers and users create new features simply by writing new prompts, while emergent capability means the agent can tackle unexpected tasks based on user requests. Improvement over time focuses on how agents can refine their performance through accumulated context and prompt adjustments without needing code updates. In practice, these principles help shape the development of applications. For instance, a notes app must allow the agent to perform actions like creating and tagging notes just as the user can. The article stresses the importance of flexible, granular tools that empower the agent to make decisions, contrasting this with less effective, bundled tools that limit adaptability. As patterns in user requests emerge, developers can optimize their tools accordingly. Ultimately, the approach encourages a foundation for product development that learns from user interactions rather than trying to predict every feature upfront.