Devika Tutorial: Open-Source Autonomous AI Software Engineer

March 2, 2026 · View on GitHub

Learn how to deploy and operate stitionai/devika — a multi-agent autonomous coding system that plans, researches, writes, and debugs code end-to-end.

Why This Track Matters

Devika represents one of the most complete open-source implementations of an autonomous software engineering agent, combining multi-agent coordination, live web research, browser automation, and polyglot code generation in a single self-hosted stack. As teams evaluate autonomous coding systems for internal use, understanding how Devika's agent pipeline is structured, how it coordinates specialized roles, and how to govern it safely becomes a critical engineering competency. This track takes you from first install to production-grade team deployment, covering every architectural layer in depth.

This track focuses on:

deploying and configuring Devika with any major LLM provider including Claude 3, GPT-4, Gemini, Mistral, Groq, and Ollama
understanding the multi-agent pipeline: planner, researcher, coder, action, and internal monologue agents
operating browser automation and web research capabilities safely and effectively
governing autonomous code generation at team scale with cost controls and audit discipline

Current Snapshot (auto-updated)

repository: stitionai/devika
stars: about 19.5k

Mental Model

flowchart LR
    A[User Task Prompt] --> B[Planner Agent]
    B --> C[Researcher Agent]
    C --> D[Browser Automation / Playwright]
    D --> E[Coder Agent]
    E --> F[Action Agent]
    F --> G[Internal Monologue / Self-Reflection]
    G -->|next step| B
    G --> H[Workspace Output + Git]

Chapter Guide

Chapter	Key Question	Outcome
01 - Getting Started	How do I install Devika and run a first task?	Working baseline
02 - Architecture and Agent Pipeline	How do Devika's specialized agents coordinate?	Architecture clarity
03 - LLM Provider Configuration	How do I connect Claude, GPT-4, Gemini, Ollama, and others?	Provider flexibility
04 - Task Planning and Code Generation	How does Devika decompose tasks and generate code?	Reliable code output
05 - Web Research and Browser Integration	How does Devika research the web with Playwright?	Research agent control
06 - Project Management and Workspaces	How do I manage projects, files, and git integration?	Workspace discipline
07 - Debugging and Troubleshooting	How do I diagnose failures in the agent pipeline?	Operational resilience
08 - Production Operations and Governance	How do teams deploy Devika safely at scale?	Governance runbook

What You Will Learn

how to configure and run Devika across multiple LLM providers for different cost and capability tradeoffs
how to reason about multi-agent coordination, context flow, and internal monologue loops
how to operate browser automation and research pipelines responsibly
how to govern autonomous code generation workflows in team environments with audit and rollback controls

Source References

OpenHands Tutorial — multi-agent AI software engineering OS
SWE-agent Tutorial — SWE-bench autonomous software engineering agent
Mini SWE-agent Tutorial — lightweight autonomous coding agent core
Aider Tutorial — AI pair programming in the terminal
Sweep Tutorial — issue-to-PR autonomous coding agent
BabyAGI Tutorial — foundational autonomous task-driven agent patterns

Start with Chapter 1: Getting Started.

Full Chapter Map

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