Wrong target
An agent may touch production when the human expected a dev, staging, or local environment.
Why Axiom
AI coding agents can interpret intent, generate implementation paths, connect tools, and make assumptions about access, data, approvals, or side effects. A prompt saying "do not do that" is not the same as a checked project contract.
An agent may touch production when the human expected a dev, staging, or local environment.
A token or API key may allow more than the agent actually needs for the task.
Generated code, tests, or status reports can look plausible while hiding missing checks or unsafe behavior.
Prompts, README files, AGENTS.md files, and team instructions are useful, but they are guidance. They can be ignored, contradicted, forgotten, or interpreted differently by different models.
Axiom gives teams a durable place to define what the app can touch, what actions exist, when approval is required, what external tools may run, what is denied, and what evidence must be captured.
capability delete_customer_data
policy:
require_approval if production_target
or irreversible_action
deny if approval_missing
or backup_not_verified
or agent_requested_broad_delete
audit:
policy_decision
approval_state
never log raw_customer_record
Agents should not invent new data access or destructive actions while implementing a feature.
Production changes, external effects, sensitive disclosures, and irreversible operations need explicit gates.
Humans need a durable record of what happened without storing raw secrets, payment data, or private records.
Axiom is not a backup system, sandbox, deployment firewall, or production permission manager by itself. It is the application contract layer that helps humans and agents define risky behavior before implementation.
These reports are examples of the failure class. Axiom references them carefully: it could help model and test the risky capabilities, but it would not be a complete safety solution by itself.