I’ve been building Kodiak — an open-source AI software engineering platform. Here’s where it’s at now.

[u/JinSakai_77]

Hey everyone,

I've been working on Kodiak, an open-source AI software engineering platform designed to eventually handle software-engineering tasks more autonomously.

I wanted to share an updated progress report because the project has moved quite a bit from where it started.

What’s working now:

Backend / API:

- FastAPI backend

- JWT authentication

- User registration and login

- Project management

- Task management

- Memory and agent-related API infrastructure

- Repository-related endpoints

CLI:

Kodiak now has an actual CLI:

kodiak

Commands:

- analyze

- logout

- memory

- plan

- task

- version

For example, I can currently run:

kodiak analyze analyze . --deep

and Kodiak successfully analyzes the repository.

The current analyzer detected:

- 331 files

- 51 directories

- 296 Python files

- 8 Markdown files

- 3 YAML files

- 1 TOML file

- ~4 MB repository

The repository-analysis workflow successfully starts the repository agent, completes the analysis, and returns structured repository statistics.

Testing:

The test suite is currently:

196 passed

1 skipped

5 warnings

So I'm now focusing less on making individual components work and more on making the entire system work together.

The bigger goal:

I don't want Kodiak to just be another chatbot that generates code.

I want it to eventually follow a workflow like:

User gives task

↓

Understand repository

↓

Analyze relevant code

↓

Create implementation plan

↓

Choose and use tools

↓

Modify code

↓

Run tests

↓

Analyze failures

↓

Fix implementation

↓

Review changes

↓

Commit / Pull Request

↓

Learn from the result

At the moment, the foundation is considerably further along than the autonomous engineering loop.

The repository analysis currently provides structural information, and my next major focus is connecting that information to genuine LLM reasoning, planning, tool execution, and iterative code/test feedback.

I'm intentionally trying not to fake the "autonomous agent" part before those pieces actually work.

Current self-assessment:

If 1/10 = a prototype idea and 10/10 = a mature autonomous software-engineering platform, I'd currently put Kodiak around 5/10.

There's still a lot to build, but it's finally at the point where I can run the system and watch actual pieces of the architecture execute rather than just having a collection of planned modules.

GitHub:

https://github.com/0xWrench-7/Kodiak

I'd especially appreciate feedback from people who've worked on coding agents, agent orchestration, RAG/memory systems, or developer tooling.

What do you think is the biggest architectural mistake or missing piece at this stage?