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 an AI agent in simple terms?

An AI agent is a software system that uses a large language model as its "brain" to perceive its environment, plan a sequence of steps, and use tools to complete a goal — all without needing a human to guide every action. Think of it as a digital coworker that can read emails, search the web, run code, and make decisions on your behalf.

How is an AI agent different from a chatbot?

A chatbot responds to one prompt at a time and has no memory between turns. An AI agent is goal-driven — you give it an objective, and it independently breaks the task into steps, uses tools, observes results, and iterates until the job is done. See our full [comparison of AI agents vs. chatbots](/blog/ai-agents-vs-chatbots/) for details.

What tools can AI agents use?

AI agents can call any tool exposed via an API or function: web search, code execution, database queries, file manipulation, sending emails, filling forms, controlling a browser, and more. The tool-calling mechanism is what gives agents real-world reach beyond language.

Are AI agents ready for production use?

Yes — with the right guardrails. As of 2026, 79% of employees report their companies are using AI agents. Production deployments require activity logging, loop limits, human-approval gates for high-stakes actions, and robust error handling. Most enterprise agents are advisory first, fully autonomous second.

What frameworks do developers use to build AI agents?

The most popular frameworks in 2026 are LangChain, LangGraph, CrewAI, AG2 (formerly AutoGen), and the OpenAI Agents SDK. Each has trade-offs around flexibility, multi-agent support, and observability. See our [framework comparison](/blog/ag2-vs-crewai-vs-langgraph-openai-agents-sdk/) for a detailed breakdown.

AI Agents Explained: From Concept to Production

AI agents explained in plain English. How they work, what sets them apart from chatbots, and how teams use them TODAY. Examples + tips.

Frequently Asked Questions

What is an AI agent in simple terms?: An AI agent is a software system that uses a large language model as its "brain" to perceive its environment, plan a sequence of steps, and use tools to complete a goal — all without needing a human to guide every action. Think of it as a digital coworker that can read emails, search the web, run code, and make decisions on your behalf.
How is an AI agent different from a chatbot?: A chatbot responds to one prompt at a time and has no memory between turns. An AI agent is goal-driven — you give it an objective, and it independently breaks the task into steps, uses tools, observes results, and iterates until the job is done. See our full [comparison of AI agents vs. chatbots](/blog/ai-agents-vs-chatbots/) for details.
What tools can AI agents use?: AI agents can call any tool exposed via an API or function: web search, code execution, database queries, file manipulation, sending emails, filling forms, controlling a browser, and more. The tool-calling mechanism is what gives agents real-world reach beyond language.
Are AI agents ready for production use?: Yes — with the right guardrails. As of 2026, 79% of employees report their companies are using AI agents. Production deployments require activity logging, loop limits, human-approval gates for high-stakes actions, and robust error handling. Most enterprise agents are advisory first, fully autonomous second.
What frameworks do developers use to build AI agents?: The most popular frameworks in 2026 are LangChain, LangGraph, CrewAI, AG2 (formerly AutoGen), and the OpenAI Agents SDK. Each has trade-offs around flexibility, multi-agent support, and observability. See our [framework comparison](/blog/ag2-vs-crewai-vs-langgraph-openai-agents-sdk/) for a detailed breakdown.