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AI Agents · Lesson

SWE-Agent and OpenDevin Architectures

Tour the source code of two leading open coding agents to see how the pros structure tool surfaces and prompts.

SWE-Agent and OpenDevin Architectures is a free AI Agents lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the AI Agents learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

Why Study Existing Agents?

SWE-Agent and OpenDevin (now OpenHands) are leading open-source coding agents. Reading their code teaches you what the pros do.

SWE-Agent (Princeton)

SWE-Agent introduced the "Agent-Computer Interface" (ACI) concept — a tightly designed CLI for the agent to manipulate code.

SWE-Agent Tool Surface

  • open / goto / scroll_up / scroll_down — file viewer
  • edit — line-range editing
  • create — new files
  • find_file / search_dir — search
  • submit — finish task

The "Window" Concept

SWE-Agent only shows the model a 100-line "window" of a file at a time. Forces explicit scrolling, which surprisingly helps focus.

Lint Feedback Loop

After every edit, SWE-Agent runs a linter. If new errors appeared, the edit is rejected and the model must retry.

OpenDevin / OpenHands

OpenDevin (renamed OpenHands) is a multi-agent platform built around a docker sandbox. It supports many "agent" backends (CodeAct, BrowsingAgent, etc.).

OpenHands Tool Set

  • execute_bash — run shell
  • str_replace_editor — Anthropic-style editor
  • browse — browser tool for web research
  • finish — task complete

Action and Observation Loop

OpenHands explicitly models agent steps as Action -> Observation pairs:

{'action': 'execute_bash', 'args': {'command': 'pytest'}, 'observation': '5 failed, 3 passed', 'next_thought': 'I need to look at the failing tests.'}

CodeAct Insight

CodeAct (UIUC) showed that letting the model emit PYTHON CODE for every tool call (instead of fixed JSON tool calls) often outperforms.

Reason: code naturally composes, the model can use loops/conditions/intermediates.

OpenAI Codex CLI

OpenAI shipped Codex CLI — their open-source coding agent reference. Similar pattern: editor, shell, search, finish.

Common Architectural Patterns

  1. Sandboxed Docker workspace per task
  2. Read / edit / run / search tool set
  3. Per-edit verification (lint or test)
  4. Step caps (50-100 iterations)
  5. Trace logging for everything

Where Implementations Differ

  • Edit format: line-range vs string-replace vs full-file
  • File viewer: windowed scroll vs jump-to-line
  • Memory: scratchpad vs system-prompt notes
  • Verification cadence: per-step vs at-end

Build Your Own

You can build a competitive coding agent in 500-1000 lines of Python by combining:

  • The tools from Lesson 2
  • The fix loop from Lesson 3
  • A planning step from Lesson 1
  • Sandboxing from Course 23
  • Eval from Course 21

Read the Source

Both SWE-Agent and OpenHands are public on GitHub. Spend an afternoon reading their main loops — best education in agent engineering you can get.

Common Design

What is a near-universal architectural pattern across coding agents?

Recap

SWE-Agent's ACI, OpenHands' action-observation loop, CodeAct's code-as-action. Read their source. Borrow what works. Build your own slimmer version.

Frequently asked questions

Is the “SWE-Agent and OpenDevin Architectures” lesson free?

Yes — the full text of “SWE-Agent and OpenDevin Architectures” is free to read here on the web, and the AI Agents course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the AI Agents course, upgrade to CoddyKit PRO.

What will I learn in “SWE-Agent and OpenDevin Architectures”?

Tour the source code of two leading open coding agents to see how the pros structure tool surfaces and prompts. You practise AI Agents with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start AI Agents?

No prior experience is required. AI Agents on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “SWE-Agent and OpenDevin Architectures” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this AI Agents lesson?

Yes. Every AI Agents lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

All lessons in this course

  1. Agentic Patterns: Plan-Execute-Verify
  2. Tool Surfaces for Coding (Read, Edit, Bash)
  3. Iterative Self-Correction Loops
  4. SWE-Agent and OpenDevin Architectures
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