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.

Blog — Page 2 — cowork.ink

Insights on AI agents, automation, developer tooling, and human–AI collaboration. Guides, tutorials, and industry analysis from the cowork.ink team.

Articles - Page 2

Autonomous AI Agents: How They Decide, Act & Learn - Autonomous AI agents perceive their environment, reason about goals, and execute multi-step tasks without human hand-holding. This guide explains how they work, what makes them different, and how teams deploy them in 2026.
Best AI Agent Platforms in 2026: Top 10 Compared - Looking for the best AI agent platforms? We tested and compared 10 leading platforms — from no-code builders to developer frameworks — so you can pick the right one for your team.
Best AI Code Review Tools: Top 7 Compared (2026) - AI code review tools cut review time by 40-60% and catch bugs humans miss. We tested the top 7 tools and compared features, pricing, accuracy, and platform support to help your team choose.
Best MCP Servers in 2026: 20 Must-Install Integrations - The MCP ecosystem has exploded to 5,500+ servers. These are the 20 best MCP servers that developers actually use in production — organized by category with install instructions and honest trade-offs.
Build an AI Agent in Python: Complete Tutorial with Code - Learn how to build an AI agent in Python from scratch — no frameworks required. This step-by-step tutorial covers tool calling, memory, the agent loop, and when to reach for a framework instead.
Claude Code Review for Pull Requests: Setup Guide - Claude Code Review uses multi-agent analysis to catch logic errors, security vulnerabilities, and regressions in your pull requests. Here's how to set it up, what it costs, and whether it's worth the price.
GitHub Copilot Coding Agent: What It Does & How to Use It - GitHub Copilot coding agent works autonomously in the background — fixing bugs, adding tests, and opening pull requests without you watching. Here's what it does, how to set it up, and when to use it.
How Do AI Agents Work? Architecture, Loops & Examples - How do AI agents work under the hood? This guide breaks down the perceive-reason-act loop, core architecture components, and real-world examples that show how modern agents think, decide, and take action.
How to Build an AI Agent: Practical Guide for 2026 - Learn how to build an AI agent from scratch — from defining goals and picking a framework to deploying in production. A step-by-step guide covering code, no-code, and framework approaches.
LangChain Tutorial: Build Your First AI Agent Step-by-Step - Learn how to build your first AI agent with this hands-on LangChain tutorial. From installation to deploying a working ReAct agent with custom tools — everything you need to get started in Python.
MCP Security: How to Lock Down AI Agent Tool Access - MCP security best practices are critical as AI agents gain access to production tools and data. Learn how to lock down tool access, prevent prompt injection, and enforce least privilege across your MCP servers.
Multi-Agent Collaboration: How AI Teams Solve Complex Tasks - Multi-agent collaboration lets specialized AI agents divide, conquer, and coordinate complex tasks that no single agent can handle alone. Learn how these AI teams work, when to use them, and which patterns deliver results.

Blog — Page 2 — cowork.ink

Articles - Page 2

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