Building AI Agents
Overview
Building AI agents involves creating autonomous systems that can analyze information, make decisions, and perform tasks with minimal human input. These agents rely on artificial intelligence models and structured frameworks to process data, engage with users, and execute actions. Development typically involves selecting a platform that supports natural language understanding, decision-making, and automation. Various frameworks exist to help structure these agents, allowing them to retrieve information, interact with external systems, and improve their responses over time.
Platforms vs. Frameworks
Platforms and frameworks both play essential roles in software and AI development, but they serve different purposes.
• Agent Platforms:
Platforms are broader environments that provides the infrastructure and tools needed to build, deploy, and manage applications. It often includes pre-built services, cloud computing resources, and integration capabilities that allow developers to create and run software efficiently. Platforms are designed to support entire ecosystems, enabling seamless connectivity between different tools, data sources, and services.
• Agent Frameworks:
Frameworks, on the other hand, are structured foundations for building specific types of applications. It provides reusable components, predefined architectures, and best practices that help streamline development. Unlike platforms, frameworks do not typically offer hosting or full-service environments; instead, they guide how applications should be built and structured. While platforms focus on providing an operational environment, frameworks ensure consistency and efficiency in development, making them a crucial part of software engineering and AI system design.
Find the best Platforms and Frameworks for you
Explore our curated collection of the top Agent Platforms and Frameworks on the market so you can easily start building your AI Agents.
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