A good AI coding assistant policy fits on one page and answers five questions: which tools are approved, what data may go into them, what an agent may run, who reviews the output, and how incidents are reported. Anything longer goes unread. Anything unenforceable is a wish.
Why write one now?
Developers already use these tools, approved or not. NIST's SP 800-218A applies secure development practices to generative AI work, and the OWASP list for LLM applications names excessive agency and sensitive data exposure among the main risks. A policy turns those general warnings into rules your team can follow on Monday.
What should the policy say?
Approved tools and accounts. Name the tools and require company accounts, not personal ones, so that retention and training terms are the ones you reviewed. Say what happens with unapproved tools.
Data rules. Define what must never be pasted or exposed: secrets, customer data, unreleased security fixes, regulated data. Say whether private repositories may be indexed. Be explicit about files the tool should not read, and use ignore files.
What agents may do. For tools that run commands or edit across files, say which actions need human approval: shell commands, network access, package installs, deploys. State that agents do not use personal credentials with broad reach.
Review and ownership. The developer who commits the code owns it. AI-assisted changes go through the same review and CI as any other change, and reviewers check dependencies and trust boundaries with extra care. No AI-only merges to protected branches.
Licensing and provenance. Say how you handle code that may be copied from other sources, and who to ask.
Incidents and exceptions. If a secret is pasted into a tool or an agent does something unexpected, who gets told, and how fast? Make it easy to report without blame.
What does a short version look like?
A constructed example, five lines a team could pin in the repository: Use only the approved assistants on company accounts. Never paste secrets, customer data or unreleased vulnerability details. Agents ask before running commands or installing packages. You own what you commit, and it gets the same review and scans. Report mistakes in the security channel within a day, no blame.
Short rules get followed. Link the longer standards and exceptions process beneath them.
How do you enforce it?
Pair each rule with a control. Enforce settings centrally where the tool allows. Use secret scanning on commits. Run dependency scanning and policy gates in CI so a bad package or a missing review blocks the merge. Log tool usage where possible.
How do you handle shadow use?
People will try tools you have not approved, especially when approved ones are slow or limited. Ask about it openly instead of punishing it. A short survey or a conversation in a team meeting usually reveals which tools are in use and why. Often the reason is a missing capability you can add to the approved set.
Then make the approved path the easy one: provision accounts quickly, document setup in five minutes, and publish a fast exception process for trying a new tool. Pair that with light detection, such as noticing unfamiliar assistant extensions in managed editors or domains in proxy logs where you already have them. The goal is visibility, not surveillance.
How to check or apply this
- List the assistants in use, including unofficial ones, by asking and by checking network and billing data.
- Review each approved tool's data handling terms and admin controls.
- Write the one-page policy covering the six areas above.
- Map each rule to a technical control or a review step.
- Train developers with two real examples of mistakes, not a slide deck.
- Review the policy every six months as tools change.
Safeguard's policies and gates, IDE extensions and MCP Guardrail can enforce several of these rules in the developer workflow.
Quick check
Should we ban AI assistants?
Bans tend to push use into personal accounts you cannot see. A narrow approved set with clear rules is usually safer.
Who owns AI-written code?
For accountability, the developer who commits it. For legal ownership and licensing questions, ask counsel.
Sources
Last reviewed: 18 October 2026.
