Definition
LLM using tools in a loop with context
Not marketing fluff about “autonomous systems.” An agent is an LLM that can use tools, runs in a loop until the task is done, and keeps context across iterations. This is the definition that changes how you think about AI.
while(task) { think → act → observe }The Difference
Agentic AI vs Conversational AI
AGENTIC AI
LLM + Tools + Loop + Context
while(task) { think → act → observe }CONVERSATIONAL AI
Single prompt, single response
prompt → response → doneEvolution
The Rise of Agentic Coding
Anthropic released Claude Code — the first terminal agent that could navigate codebases, run tests, and ship changes autonomously.
Cursor shipped “agents in your terminal” 11 months later. The rest of the industry scrambled to catch up.
Teams who master agentic workflows ship 3-5x faster. The gap between those who use AI conversationally and those who use it agentically is growing every month.
Advantage
Why Terminal Agents Win
IDE agents are sandboxed. Terminal agents have full system access.
Hooks for pre/post actions. Custom MCP servers. Integration with any CLI tool.
Write and execute bash scripts. Configure AWS/GCP/Azure via CLI. Infrastructure as code.
Git hooks and pre-commit. CI/CD automation. Build and deploy workflows.
File system operations. Process management. Network and API calls.
Breakthrough
The Learning Loop
while(task) { think → act → observe }
The loop naturally learns through iteration. Each cycle's "think" is informed by the previous cycle's "observe" — that is reflection. The iteration itself creates learning.
“After writing my first LLM loop, I couldn't sleep. Every repetitive task, every debugging session, every code review — I could see how each one could be transformed.
Once you build your first loop, you stop thinking about AI as a chatbot. You start seeing it as a collaborator that improves with each iteration. That's the shift.”
Kaido Koort
Ready to Assemble Your Harness?
6 weeks. Assemble the agentic harness around Claude Code — tools, context, and workflows that grow with your codebase.
View Full ProgramNot ready to commit? Talk to Kaido about a hackathon for your team.