Python developer reins in Claude Code: an open-source config against regressions

A developer at CREATMAN spent several weeks studying the documentation, Reddit discussions and other people's setups to put together a Claude Code configuration with real protection against regressions. The result is an open repository with ready-to-use files.

A problem everyone knows

Claude Code is powerful, but without proper setup it acts too independently. A typical picture for a solo developer:

• You ask it to add authentication, and the agent rewrites half the project
• You ask it to fix one function, and you get deleted tests and an unrequested dependency
• You build a working prototype in an hour, then spend three hours untangling the agent's "improvements"

For people who work alone, this is doubly critical. There is no QA engineer to catch regressions after every prompt. There is no reviewer to notice deleted tests. Every unplanned edit costs time spent sorting through someone else's decisions instead of working on the product.

The author runs CREATMAN without a team and ran into exactly this: AI helps build fast, but without control it creates new problems just as fast.

What the configuration consists of

After several weeks of reading docs, forum discussions and analyzing other people's setups, the author settled on five key components. All of them are in the claude-code-antiregression-setup repository and ready to use:

• CLAUDE.md: the main contract file, covering task scope, explicit bans on independent decisions, and a requirement to describe upcoming changes before making them
• Directory rules: folder-level restrictions so the agent does not touch anything it was not explicitly asked to
• Mandatory checklist: before any change, the agent describes its plan, and the developer approves or rejects it
• Hooks: automatic scripts that run after every agent action and check that it matches the task
• Prompt templates: ready-made request formats that remove ambiguity and narrow the room for interpretation

Importantly, everything is documented. The repository is meant not for study but for quick adoption: clone it, adapt it to your project, use it.

Why a contract works better than a ban

The key idea is to give the agent clear rules rather than simply restrict it. Claude Code reads CLAUDE.md at the start of every session. If the file explicitly says "don't touch tests without a request," "make changes only within the specified files" or "warn before adding a dependency," the agent follows it.

"I need the AI agent to help me ship faster, not create new problems,"

the author says, explaining the goal.

Hooks add a second layer. Small scripts run after changes and check whether the agent has stepped out of bounds. If it has, the changes are flagged for review instead of silently entering the codebase.

Prompt templates solve a different problem. A vague request gives the agent too much room for interpretation, and that is where freelancing begins. Ready-made formats that specify scope, files and expected result narrow that room sharply.

CLAUDE.md is not just a README for the agent but a living project document. It records architectural decisions, critical modules and naming conventions. The agent uses the file as context for every request, which makes its understanding of the project more concrete and random "improvements" less likely.

The configuration is not tied to a specific stack. The author works with a Python backend, but the principles apply to any project where you need to keep the agent within the bounds of the assigned task.

What this means

Unpredictability is one of the main barriers to adopting AI agents in solo development. Open configs like this one lower the entry threshold: you take the structure, adapt it to your project and get a manageable tool instead of a chaotic assistant. The more such setups appear in the open, the more practical it becomes to use AI agents without a support team.