The Tech Stack: Building Blocks of a Successful AI Agent

When it comes to AI agent development, there are many layers to keep in mind.  Getting familiar with the AI agent tech stack can help developers master these layers, implementing useful tools as they create and polish AI agents. 

The tech stack is composed of various tools which allow AI agents to reason and act.  These tools work together in specific ways, creating an interconnected web.  However, there is a foundation to this larger web: data collection and integration. 

Understanding data collection and integration–the foundational layer of the tech stack–is the perfect starting point for developers.  Data collection and integration provides agents with high quality real-time data.  This data informs the agent about important contexts in which the agent operates.  Without this data, the AI agent would not be able to perform tasks and adapt. 

Once a foundation of data has been established, the developer can tackle the rest of the tech stack.  There are many layers to take into account, such as vertical agents, observability, agent frameworks, memory and more.  Each of these layers has a plethora of platforms that developers can use.  For example, when it comes to memory, developers often use services such as ChromaDB or Weaviate.

The AI agent tech stack is useful in guiding development, as it lays out the foundation and building blocks of successful agents.

Source: Bright Data