AI Agents 101 with OpenClaw and Cowork - Build structure of AI agents that research, act, and execute
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AI Fire: AI Agent Fundamentals is a practical video playbook that explains what AI agents are, why they matter, and how they actually work. Instead of just talking theory, the video breaks down the core building blocks of agents — goals, tools, memory, context, planning, and permissions — then shows real demos using Claude Cowork and OpenClaw. It helps creators, founders, and operators understand when to use each tool and how to build safer, more useful AI workflows.
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Hey Product Hunt 👋
I made this launch for anyone who keeps hearing about “AI agents” but still feels like the explanation is either too technical or too vague.
In this AI Fire video, I break down the fundamentals of AI agents in a practical way:
- What an AI agent actually is
- Why agents are different from normal chatbots
- The core parts every agent needs: goals, tools, memory, context, planning, and permissions
- Why access and safety matter so much
- Real demos with Claude Cowork and OpenClaw
- When to use Claude Cowork vs when to use OpenClaw
The goal is to make AI agents feel understandable, useful, and less overhyped.
Claude Cowork feels great for knowledge work like research, files, reports, and business deliverables.
OpenClaw feels more like a personal assistant layer that can connect across apps, channels, and automation workflows.
Would love to know: which one would you try first — Claude Cowork or OpenClaw?