What AI models does the agent use?

The agent has access to Claude, DeepSeek, Gemini, and other top models. It automatically routes to the best model for each task — you never have to think about API keys or token limits.

Yes. Each agent runs in an isolated environment. We don't train on your data, and you can export or delete everything at any time. The underlying engine (GoGogot) is open-source, so you can audit exactly how it works.

What can the agent actually do?

Browse the web, process files (CSV, PDF, images), run scheduled tasks, remember context across sessions, and communicate via Telegram or Slack. Think of it as a capable junior employee, not a chatbot.

How does memory work?

The agent maintains persistent memory across sessions. It remembers your preferences, past conversations, and task context. You can also explicitly tell it to remember or forget things.

Can I self-host the agent?

Absolutely. GoGogot is 100% open-source. Run it on your own hardware for free. cowork.ink is the managed version — we handle servers, model costs, updates, and uptime so you don't have to.

Is there a free trial?

We offer a 7-day money-back guarantee. Spin up an agent, give it real tasks, and if it doesn't save you time, we'll refund you — no questions asked.

What is the agent loop in AI?

The agent loop is a repeating cycle where an AI agent perceives its environment, reasons about the next step, takes an action, observes the result, and repeats. It's the core mechanism that makes agents autonomous. Learn more in our [ReAct pattern guide](/blog/react-pattern-ai-agents/).

How do AI agents make decisions?

AI agents make decisions using an LLM as their reasoning engine. The model receives the current context — goal, conversation history, tool outputs, and memory — then selects the best next action from available tools. This is called agentic reasoning.

What are the main components of an AI agent?

The main components are a perception layer (input processing), a reasoning engine (usually an LLM), memory (short-term and long-term), tools (APIs and functions the agent can call), and an orchestration layer that ties everything together in a loop.

What is the difference between AI agents and chatbots?

Chatbots generate a single response to each message. AI agents run autonomous loops — they plan multi-step workflows, call external tools, and adapt based on results. See our full [AI agents vs. chatbots comparison](/blog/ai-agents-vs-chatbots/).

Do AI agents need to be trained?

Most modern AI agents don't require custom training. They use pre-trained LLMs (like GPT, Claude, or Gemini) and gain capabilities through prompt engineering, tool definitions, and memory systems rather than fine-tuning model weights.

How Do AI Agents Work? Architecture, Loops & Examples

Learn how AI agents work — the perceive-reason-act loop, core components, and real examples. COMPLETE guide to agent architecture in 2026.

Frequently Asked Questions

What is the agent loop in AI?: The agent loop is a repeating cycle where an AI agent perceives its environment, reasons about the next step, takes an action, observes the result, and repeats. It's the core mechanism that makes agents autonomous. Learn more in our [ReAct pattern guide](/blog/react-pattern-ai-agents/).
How do AI agents make decisions?: AI agents make decisions using an LLM as their reasoning engine. The model receives the current context — goal, conversation history, tool outputs, and memory — then selects the best next action from available tools. This is called agentic reasoning.
What are the main components of an AI agent?: The main components are a perception layer (input processing), a reasoning engine (usually an LLM), memory (short-term and long-term), tools (APIs and functions the agent can call), and an orchestration layer that ties everything together in a loop.
What is the difference between AI agents and chatbots?: Chatbots generate a single response to each message. AI agents run autonomous loops — they plan multi-step workflows, call external tools, and adapt based on results. See our full [AI agents vs. chatbots comparison](/blog/ai-agents-vs-chatbots/).
Do AI agents need to be trained?: Most modern AI agents don't require custom training. They use pre-trained LLMs (like GPT, Claude, or Gemini) and gain capabilities through prompt engineering, tool definitions, and memory systems rather than fine-tuning model weights.