Use case
Python for AI development with tested pull requests
Python teams across data, ML, and backend move fast, but the test-and-PR loop still takes time. Agentcode runs PyTest and opens the PR for you.
In short
Agentcode is an autonomous AI coding agent built for Python teams doing data, ML, and backend work, including Python for AI development. You describe a task, and it plans the change, edits your Python code, runs PyTest, and opens a pull request you review and merge. It is review-first and never merges on its own, so a human always approves the change before it lands. It works on your existing GitHub or GitLab repo and CI, and it never trains on your code.
The problem
Writing the code is the quick part; running PyTest, fixing what broke, and packaging it into a clean PR is what drags.
How Agentcode helps
Hand Agentcode a Python task and let it run the full loop your team usually does by hand. It plans the change, edits the modules, runs PyTest, and fixes what the failures reveal until the suite is green, then opens a pull request with the diff and the test results. Your team reviews the Python the same way you review any colleague's work and merges when it is right. You move data, ML, and backend tickets forward faster while keeping a human gate on everything that reaches your main branch.
What the agent brings to this work
See it run
From task to pull request
Pick a task
Plan
- planning
Files changed
Test run
Pull request
You review and merge. Agentcode never merges on its own.