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Automated AI Agents - Free Workflows

Discover 15 free step-by-step AI workflows to automate your tasks with ChatGPT, Claude and Gemini.

🤖AutomatisationIntermediate

OpenClaw: open-source autonomous AI agent framework

OpenClaw has become the open-source reference for autonomous AI agents in just a few months, with over 250,000 GitHub stars. The framework runs locally on your machine or server under an MIT license, with zero vendor lock-in. Its ClawHub ecosystem gathers 13,000+ reusable skills and offers native integrations with Telegram, Discord, Slack and WhatsApp. The project, launched by Peter Steinberger (hired by OpenAI in February 2026), embodies the self-hosted AI agent trend. For developers seeking a serious alternative to proprietary agents, OpenClaw delivers a rare balance: full autonomy, extensibility via skills, and privacy since everything runs on your own infrastructure.

6 steps
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🤖AutomatisationIntermediate

Hermes Agent: the AI agent that grows with you

Hermes Agent is an open-source AI agent launched by Nous Research on February 25, 2026, which racked up over 57,000 GitHub stars in six weeks. Its promise: an agent that grows with you through persistent memory and auto-generated skills. Unlike static agents, Hermes runs a self-improving loop: it observes failures, detects patterns, and creates new skills to handle future cases. It supports the agentskills.io open standard, making it interoperable with OpenClaw. Hermes works with 15+ messaging platforms and ships under the MIT license. It's the pick of developers who want a truly adaptive agent, not just another LLM wrapper.

6 steps
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🤖AutomatisationIntermediate

NanoClaw: the lightweight containerized OpenClaw

NanoClaw is the minimalist, containerized version of OpenClaw. Same open-source philosophy, same ClawHub ecosystem, but with a smaller footprint and a Docker-first approach. Where OpenClaw targets developers wanting a full ecosystem, NanoClaw is for those who want a ready-to-go AI agent in seconds: `docker run` and you're set. Ideal for edge computing, Raspberry Pi or Kubernetes setups. NanoClaw shares the same MIT license and skill standard as its big brother, making it easy to move to full OpenClaw when your needs grow.

5 steps
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Clawdbot: the privacy-first personal AI assistant

Clawdbot is the consumer version of the OpenClaw ecosystem, built for users who want a powerful yet privacy-respecting AI assistant. Marketing tagline: a Claude with hands, without cloud dependency. The assistant installs on your machine or a personal server and lives where you already chat: Telegram, Signal, WhatsApp. It can run real actions (calendar, email, scripts, automated purchases) without ever sending your data to a third-party provider. Clawdbot offers a serious alternative to proprietary US assistants: same agentic capabilities, but on your own infrastructure.

5 steps
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Devin 2.0: the AI software engineer coding autonomously

Devin 2.0 is the second iteration of the AI software engineer from Cognition Labs. It runs in a full cloud sandbox with IDE, web browser and terminal, and can deliver complete pull requests to your repos. The drop from $500/mo to $20/mo (plus ACU consumption, Agent Compute Units) made Devin accessible to the mainstream. V2 introduces Devin Wiki, which auto-indexes your repos to surface relevant context, plus Interactive Planning, which makes you validate the plan before execution. For teams looking to delegate full tickets to an AI without babysitting, Devin 2.0 is probably the most polished offer on the market today.

6 steps
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Cursor 3: the AI-native IDE with parallel agents on git worktrees

Cursor 3 crossed $500M ARR and became the reference AI IDE among developers. It's a VS Code fork designed around AI: ultra-fast tab completion, agent mode, composer for multi-file refactors. The v3 headline: parallel agents. Up to 8 agents can run concurrently on different parts of your codebase via git worktrees, avoiding conflicts and parallelizing independent tasks (e.g., one agent on tests, one on docs, one on a back-end refactor). Cursor remains the go-to tool for developers who want to stay in a classic IDE while leveraging the latest models (Claude Sonnet, GPT, Gemini) with fine-grained orchestration.

6 steps
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🤖AutomatisationIntermediate

Kiro: spec-driven coding agent with phase-by-phase approval

Kiro is a coding agent that pushes back on full autonomy: it uses a spec-driven approach where each phase (requirements, design, execution) is validated by the developer before moving on. This philosophy attracts teams that want strong control over the AI's direction, especially in regulated or complex contexts. Kiro is a single-thread IDE agent, not a swarm of parallel agents: the idea is a disciplined companion, not a horde. Native AWS integration (IAM, Lambda, CDK) makes it a natural fit for teams already in the Amazon ecosystem. Structured oversight cuts the usual drift risk of fully autonomous agents.

6 steps
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🤖AutomatisationIntermediate

Sculptor: parallel agents isolated in local Docker containers

Sculptor flips the Devin model: instead of a single autonomous agent in an opaque cloud sandbox, Sculptor launches multiple AI agents in parallel inside local Docker containers that you watch and control. Each agent works on a distinct part of the codebase in its own isolated environment. You can open a shell in the container, check the logs, stop the agent, or restart it with a new instruction. Container isolation also avoids conflicts between agents. Target audience: Mac and Linux developers who want the power of parallel agents without handing control to a cloud vendor. Great option for privacy-sensitive teams.

6 steps
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🤖AutomatisationIntermediate

Cline: the terminal-first open-source coding agent, MCP-native

Cline is the open-source reference for developers who want a controlled, transparent, terminal-first coding agent. The project is one of the first to make the Model Context Protocol (MCP) a first-class citizen. Unlike Cursor or Devin, Cline charges nothing: you bring your own LLM key (Anthropic, OpenAI, DeepSeek, local models via Ollama) and only pay for API calls. The tool shows real-time cost of each action, a favorite feature for cost-conscious development. Distributed as a VS Code extension or standalone client, Cline stands out for its readability (every shell command is explicit) and its MCP ecosystem letting you plug custom tools in a few lines. Particularly well-suited to experienced developers who want to understand and control every step.

6 steps
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🤖AutomatisationIntermediate

CI/CD Pipeline Creation

This agent generates complete and optimized CI/CD pipeline configurations for your tech stack. It covers continuous integration (lint, tests, build), continuous delivery (staging, production) and includes security, caching and notification best practices. Compatible with GitHub Actions, GitLab CI, and more.

3 steps
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Figma Design to Code Conversion

This agent converts your Figma mockup descriptions into production-ready frontend code. It generates structured React/Vue/HTML components, responsive CSS (Tailwind or CSS modules), handles mobile/desktop breakpoints and produces accessible, maintainable code following modern best practices.

3 steps
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Unit Test Generation

This agent analyzes your source code and automatically generates a comprehensive unit test suite. It identifies nominal cases, edge cases, error cases and regression scenarios. Generated tests follow the chosen test framework best practices and aim for maximum coverage.

3 steps
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