Explainers
aaaa.fyi · 2026-07-23 · 7 min read
Agentic AI is software that pursues a goal through multiple steps on its own: it plans, takes actions with tools, checks the results, and keeps going until the job is done. A chatbot answers your question; an agent finishes your task.
An AI agent is a loop wrapped around a language model with four parts:
Remove any one of these and you're back to a chatbot: smart, but hands-off.
Ask a chatbot "why is my build failing?" and you get a guess based on your description. Give an agent the same question and it *runs the build*, reads the actual error, opens the failing file, applies a fix, and re-runs until green. Same model — entirely different system around it.
Two standards made agents practical rather than academic: MCP gave every agent the same way to use tools, and skills gave them installable, inspectable expertise. Building an agent stopped meaning "build everything" — see how to build an AI agent.
Agents fail in ways chatbots can't: they can take *wrong actions*, not just give wrong answers. Production agentic systems bound the loop (max steps, budgets), checkpoint risky actions, and keep a human on irreversible ones. Autonomy is a dial, not a switch.