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 does "agentic AI" mean?

Agentic AI describes AI systems that operate autonomously toward a goal — planning steps, calling tools, and making decisions across multiple actions without needing step-by-step human instructions. Unlike a chatbot that responds once, an agentic AI keeps working until the task is done.

What is the difference between agentic AI and regular AI?

Regular AI (like ChatGPT or Copilot) responds to a single prompt and stops. Agentic AI loops: it reasons, acts, observes the result, and repeats until it achieves a goal. Agentic AI can browse the web, write and run code, send emails, and update databases — not just generate text.

Is ChatGPT agentic AI?

Standard ChatGPT is not agentic — it answers prompts and stops. However, ChatGPT with "Agentic mode" or plugins/tools enabled can behave agentically: it can browse, run code, and chain actions. Purpose-built agentic systems go further, operating fully autonomously for minutes or hours on complex tasks.

What are examples of agentic AI in 2026?

Real-world examples include code review agents that post PR comments autonomously, support agents that resolve tickets end-to-end, research agents that gather and synthesize information, and personal briefing agents that scan email and calendar every morning. See our [AI agent examples](/blog/ai-agent-examples/) for 15 production-proven cases.

Why is 2026 called the inflection point for agentic AI?

Three forces converged in 2025-2026: LLMs became reliable enough for multi-step reasoning, tooling (MCP, LangGraph, OpenAI Agents SDK) matured, and enterprise adoption passed the proof-of-concept stage. Gartner predicts 40% of enterprise apps will feature task-specific AI agents by end of 2026 — up from under 5% in 2025.

Agentic AI: What It Means and Why 2026 Is the Inflection Point

Agentic AI explained: what it means, how it differs from ChatGPT, and why 2026 is the inflection point. CLEAR examples + practical guide.

Frequently Asked Questions

What does "agentic AI" mean?: Agentic AI describes AI systems that operate autonomously toward a goal — planning steps, calling tools, and making decisions across multiple actions without needing step-by-step human instructions. Unlike a chatbot that responds once, an agentic AI keeps working until the task is done.
What is the difference between agentic AI and regular AI?: Regular AI (like ChatGPT or Copilot) responds to a single prompt and stops. Agentic AI loops: it reasons, acts, observes the result, and repeats until it achieves a goal. Agentic AI can browse the web, write and run code, send emails, and update databases — not just generate text.
Is ChatGPT agentic AI?: Standard ChatGPT is not agentic — it answers prompts and stops. However, ChatGPT with "Agentic mode" or plugins/tools enabled can behave agentically: it can browse, run code, and chain actions. Purpose-built agentic systems go further, operating fully autonomously for minutes or hours on complex tasks.
What are examples of agentic AI in 2026?: Real-world examples include code review agents that post PR comments autonomously, support agents that resolve tickets end-to-end, research agents that gather and synthesize information, and personal briefing agents that scan email and calendar every morning. See our [AI agent examples](/blog/ai-agent-examples/) for 15 production-proven cases.
Why is 2026 called the inflection point for agentic AI?: Three forces converged in 2025-2026: LLMs became reliable enough for multi-step reasoning, tooling (MCP, LangGraph, OpenAI Agents SDK) matured, and enterprise adoption passed the proof-of-concept stage. Gartner predicts 40% of enterprise apps will feature task-specific AI agents by end of 2026 — up from under 5% in 2025.