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 agentic engineering?

Agentic engineering is a software development discipline where AI agents write the code while human engineers orchestrate, review, and validate the output. Coined by Andrej Karpathy in February 2026, it emphasizes that working effectively with AI agents requires real engineering skill — not just prompting. See our [context engineering guide](/blog/context-engineering-ai-agents/) for the related discipline of managing agent information.

How is agentic engineering different from vibe coding?

Vibe coding means prompting an AI, accepting the output, and iterating on errors without deeply understanding the code. Agentic engineering adds human oversight, testing, architecture ownership, and structured workflows. Vibe coding ships prototypes; agentic engineering ships production systems.

What skills do you need for agentic engineering?

Strong software fundamentals — architecture design, testing, code review, and system thinking. Agentic engineering disproportionately rewards senior engineers who can evaluate AI-generated code and catch subtle bugs. Tools like [cowork.ink](https://cowork.ink) help teams coordinate AI agents with built-in oversight workflows.

Will agentic AI replace software engineers?

No — but it will change what engineers do. The role shifts from writing every line of code to orchestrating agents, reviewing output, designing architecture, and ensuring quality. Gartner predicts 40% of enterprise apps will feature AI agents by end of 2026, but engineers remain essential for oversight and reliability.

What is the difference between agentic engineering and prompt engineering?

Prompt engineering is about crafting effective instructions for a single LLM interaction. Agentic engineering is about orchestrating multi-step, multi-agent workflows end-to-end — including testing, monitoring, and human review. Prompt engineering is a subset of [context engineering](/blog/context-engineering-ai-agents/), which is itself a component of agentic engineering.

Agentic Engineering: The Discipline of Building Reliable AI Agent Systems

Agentic engineering is the discipline replacing vibe coding. Learn the KEY principles, levels & practices for production AI agents. FULL guide.

Frequently Asked Questions

What is agentic engineering?: Agentic engineering is a software development discipline where AI agents write the code while human engineers orchestrate, review, and validate the output. Coined by Andrej Karpathy in February 2026, it emphasizes that working effectively with AI agents requires real engineering skill — not just prompting. See our [context engineering guide](/blog/context-engineering-ai-agents/) for the related discipline of managing agent information.
How is agentic engineering different from vibe coding?: Vibe coding means prompting an AI, accepting the output, and iterating on errors without deeply understanding the code. Agentic engineering adds human oversight, testing, architecture ownership, and structured workflows. Vibe coding ships prototypes; agentic engineering ships production systems.
What skills do you need for agentic engineering?: Strong software fundamentals — architecture design, testing, code review, and system thinking. Agentic engineering disproportionately rewards senior engineers who can evaluate AI-generated code and catch subtle bugs. Tools like [cowork.ink](https://cowork.ink) help teams coordinate AI agents with built-in oversight workflows.
Will agentic AI replace software engineers?: No — but it will change what engineers do. The role shifts from writing every line of code to orchestrating agents, reviewing output, designing architecture, and ensuring quality. Gartner predicts 40% of enterprise apps will feature AI agents by end of 2026, but engineers remain essential for oversight and reliability.
What is the difference between agentic engineering and prompt engineering?: Prompt engineering is about crafting effective instructions for a single LLM interaction. Agentic engineering is about orchestrating multi-step, multi-agent workflows end-to-end — including testing, monitoring, and human review. Prompt engineering is a subset of [context engineering](/blog/context-engineering-ai-agents/), which is itself a component of agentic engineering.