An AI agent is software that can perceive its environment, make decisions, and take autonomous actions to complete a goal – without constant human input. Unlike traditional chatbots that respond to prompts, AI agents plan, use tools, and execute multi-step workflows independently.
Ronnie Huss has been building with AI agents since 2023, across products in SaaS, content, and blockchain. This is the definitive resource on everything you need to know – from agent architectures to real-world implementation.
Key Articles
- The LangGraph SQL agent: querying databases in plain English
- What is an AI agent supervisor?
- The self-RAG pattern: when AI agents know they don’t know
- AI agents for HR: automating performance reviews
- AI Handoff Patterns: How Elite Teams Pass Context Between Tools
- CrewAI vs LangGraph vs AutoGen vs Agno
- Building a marketing strategy agent with AI
- Adaptive RAG vs standard RAG
Frequently Asked Questions
What is an AI agent?
An AI agent is software that can autonomously perceive its environment, make decisions, and take actions to complete a goal without constant human input. Unlike chatbots, agents plan and execute multi-step tasks.
What is the best AI agent framework in 2026?
The most widely used AI agent frameworks in 2026 are CrewAI (multi-agent orchestration), LangGraph (stateful workflows), AutoGen (Microsoft’s multi-agent framework), and Agno. The best choice depends on your use case.
What is a multi-agent system?
A multi-agent system uses multiple AI agents working together, each specialised for a specific task. An agent supervisor coordinates them, routing tasks and aggregating results. This enables complex workflows that no single agent could handle alone.
Can AI agents replace human workers?
AI agents augment rather than replace – they handle repetitive, structured tasks at scale. The concept of AI-multiplied teams means small teams using agents can achieve output that previously required large teams.
