Chapter 2: Architecture and Agent Pipeline

Welcome to Chapter 2: Architecture and Agent Pipeline. In this part of Devika Tutorial: Open-Source Autonomous AI Software Engineer, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.

This chapter explains how Devika's five specialized agents — planner, researcher, coder, action, and internal monologue — coordinate to transform a single user prompt into working code.

Learning Goals

• understand the roles and responsibilities of each specialized agent in the Devika pipeline
• trace the data and control flow from task submission through to workspace output
• identify how the internal monologue loop drives iterative self-correction
• reason about the architectural boundaries between agents for debugging and extension

Fast Start Checklist

1. read the architecture overview in the Devika README and docs directory
2. identify the five agent types and their input/output contracts
3. trace a single task through the pipeline by reading the orchestrator source
4. inspect agent log output for a real task to observe the coordination sequence

Source References

• Devika Architecture Docs
• Devika How It Works
• Devika Agent Source
• Devika Repository

Summary

You now understand how Devika's multi-agent architecture decomposes a high-level task into research, planning, coding, and self-reflection steps that loop until the task is complete.

Next: Chapter 3: LLM Provider Configuration

How These Components Connect

flowchart TD
    A[User task input] --> B[Planner Agent]
    B --> C[Break into subtasks]
    C --> D[Researcher Agent]
    D --> E[Web search & browse]
    E --> F[Coder Agent]
    F --> G[Generate code]
    G --> H[Action Agent]
    H --> I[Write files, run code]
    I --> J[Internal Monologue]
    J --> K[Agent state update]