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The AI Coding Security Skill File Every CTO Needs

A practical skill file for keeping AI coding agents inside clear guardrails before they touch a repo.

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The AI Coding Security Skill File Every CTO Needs

The AI Coding Security Skill File Every CTO Needs

Every AI coding tool becomes a security problem the moment it can read a repo, run commands, or touch secrets. The next CTO advantage is not faster typing. It is tighter control over what the agent can see, edit, and ship.

Most teams miss the real failure mode. They focus on model quality, then give the agent broad access. The result looks productive until one bad prompt, one stale secret, or one loose rules file turns a helper into a repo-wide intruder.

The fix is not fear. It is a skill file.

What goes wrong first

  1. Teams let the agent start before they define the lane.
  2. Teams trust summaries instead of diffs, logs, and tests.
  3. Teams give the same workflow read access, write access, and deploy access.

That last one is where the damage gets expensive. A support assistant should answer from docs. A product assistant should draft specs. A coding agent should patch code under review. When one workflow gets every permission, the company loses the ability to say no at the right time.

The 5-step security loop

1. Define the lane

Name the one job the agent can do. Keep it narrow. "Fix this bug in these two files" beats "help with the repo."

2. Separate read from write

A reader can inspect and explain. A writer can edit within bounds. A reviewer decides whether the diff ships. If one agent does all three, the handoff disappears.

3. Lock the scope before the first command

List the files, commands, and data sources the agent may touch. Then list the things it must never touch: auth, billing, deploys, customer data, and secrets unless a human pastes them in.

4. Demand evidence, not summaries

A confident paragraph means nothing without diff, logs, or tests. Ask for the proof before you ask for the recap.

5. Make rollback part of the prompt

The team should know the revert path before the agent edits anything. If the rollback is unclear, the task is too wide.

The skill file

# AI Coding Security Skill File

## Mission
Use AI to accelerate code work without widening repo, secret, or deploy risk.

## Before you start
1. State the task in one sentence.
2. List the files you may touch.
3. List the tests you will run.
4. List the data you are not allowed to access.
5. Name the reviewer.

## Working rules
- Read only by default.
- No secrets unless a human pastes them in.
- One task, one branch, one reviewer.
- Every write must produce a diff and test output.
- Stop if the task touches auth, billing, deploys, or production data.

## Before merge
- Run the narrowest test that proves the change.
- Capture the diff and command output.
- Write the rollback path in plain English.
- Confirm support can explain the change without jargon.

## Never
- Let the agent guess before scope is clear
- Let a summary replace evidence
- Give one workflow read, write, and deploy power
- Hide a failed test behind a polished recap

That file looks plain on purpose. Plain rules beat clever prompts when the system touches real work.

This helps more than engineering. Support gets safer answers. Product gets cleaner handoffs. Ops gets fewer surprise changes. Sales stops promising behavior the system cannot support.

A real CTO pattern

In fractional CTO work with overseas teams, the mess shows up at the worst time. One engineer is offline, support has the customer complaint, product wants a date, ops wants to know whether the release changed behavior. The agent should not invent a fix and spray it across the repo. It should turn the issue into a bounded diff, a test, and a rollback plan.

That is the difference between AI as a demo and AI as an operating model.

Get the Full AI Coding Security Skill File

I posted a breakdown of the full AI coding security skill file, the scope checklist, and the agent prompt guardrails on LinkedIn. Comment "Guide" on that post and I'll DM you the link directly.

Work With Me

I help engineering orgs adopt AI across their teams, not just in the code, but in how product, support, and ops work too. If you want to move faster without growing headcount, let's talk.