AI Agent
Definition
An AI agent is a software system that uses a large language model to plan and execute multi-step actions toward a stated goal. Unlike a chatbot that only converses, an agent invokes tools (send email, update calendar, query a database) and adapts based on results. The distinguishing trait is autonomy: agents act, not just answer.
The defining feature: action
A chatbot answers a question. An assistant answers and helps. An agent takes action. The boundary is who actually does the work after the conversation: with a chatbot it’s still you, with an agent it’s the system.
When you ask ChatGPT “what should I email Sarah?” it returns text. When you ask an agent the same thing, it can compose, address, and send the email — then check whether Sarah replied and follow up if she didn’t.
The technical architecture
Modern AI agents share a few components:
- An LLM as the planner (typically Claude, GPT-4, Gemini) — interprets the goal, chooses the next step
- A tool registry — defined functions the agent can call (send email, schedule meeting, search database)
- A memory layer — short-term context plus long-term state about the user
- A loop — execute action, observe result, decide next step, repeat until done or stuck
Frameworks like LangChain, LangGraph, OpenAI’s Assistants API, Anthropic’s tool use, and custom orchestration layers all implement variations of this loop.
Three categories of agents
- Task agents — narrow scope, single workflow (“schedule this meeting”, “summarize this document”). Most reliable.
- Domain agents — broader scope within an area (email triage, sales prospecting, customer support). The category alfred_ sits in.
- General agents — try to handle anything. Still unreliable in 2026, but the trajectory points here.
What separates good agents from demoware
Three things, in order of importance:
- Reliable tool use. The agent has to actually do what it claims. Most agent demos look impressive in controlled conditions and fail on real-world edge cases.
- Bounded autonomy. The agent knows what it can do alone vs what needs human approval. Sending an internal Slack message is different from sending a customer-facing email.
- Persistent state. The agent remembers context across sessions — your tone, your priorities, your relationships.
Where alfred_ fits
alfred_ is a domain agent for email, calendar, and tasks. It reads your inbox overnight, triages by urgency, drafts replies in your voice, extracts commitments, and surfaces a Daily Brief in the morning. The agent does the planning and execution; you do the approval and any high-judgment decisions. Bounded autonomy: drafts wait for your approval before sending.
What an AI agent isn’t
It isn’t an AGI. It isn’t a chatbot with extra steps. It isn’t a workflow automation tool (Zapier) that follows fixed scripts. The defining feature is the LLM-driven planning loop that decides what to do next based on context, not a pre-defined trigger.