Agentic AI

Agentic AI refers to artificial intelligence systems that can independently plan, make decisions, and carry out tasks to achieve a goal.

What is agentic AI?

Agentic AI refers to artificial intelligence systems that can independently plan, make decisions, and carry out tasks to achieve a goal. Unlike traditional AI models that only respond to prompts, agentic AI can take multiple actions, adapt to changing information, and use software tools or external systems to complete complex workflows.

Agentic AI is designed to operate with a greater degree of autonomy while still working within defined objectives or constraints.

How does agentic AI work?

Agentic AI combines AI models with planning, reasoning, memory, and tool usage.

It can:

  • Break complex tasks into smaller steps
  • Make decisions based on available information
  • Use external tools, software, or data sources
  • Adjust its actions as conditions change
  • Continue working until a task is completed or a goal is reached

Many agentic AI systems are built using large language models (LLMs) together with additional software components.

How is agentic AI used in practice?

Agentic AI is used across a wide range of industries.

Examples include:

  • Automating customer support and business workflows
  • Conducting research across multiple sources
  • Managing software development or IT operations
  • Assisting with financial analysis and reporting
  • Performing repetitive administrative tasks with minimal human intervention

The technology is often used where tasks involve multiple steps rather than a single response.

What are notable examples of agentic AI?

Examples include:

  • AI assistants that can schedule meetings, send emails, and manage tasks
  • AI software development agents that write, test, and improve code
  • Research agents that collect, organize, and summarize information from multiple sources
  • Enterprise AI systems that automate business processes across different software platforms

These systems differ from traditional chatbots because they are designed to complete objectives, not just answer questions.

How does agentic AI relate to the crypto world?

Agentic AI is increasingly being explored within the crypto industry.

Examples include:

  • Automating trading and portfolio management strategies
  • Managing decentralized finance (DeFi) positions based on predefined rules
  • Assisting with blockchain security monitoring and smart contract analysis
  • Performing on-chain data analysis and market research
  • Interacting with decentralized applications (dApps) and blockchain protocols

Several blockchain projects are also developing infrastructure designed to support autonomous AI agents.

Why is agentic AI important?

Agentic AI is important because it expands AI from generating information to completing tasks autonomously. By combining reasoning, planning, and tool usage, agentic AI can automate more complex workflows across industries, including finance, software development, and digital assets.