Too much permission
An agent may use credentials, records, APIs, or environments more broadly than intended.
AI agents can write code faster than teams can review boundaries.
They do more than autocomplete code. They can create files, wire services, connect APIs, change workflows, and touch data. Prompt instructions help, but they are not an enforcement boundary.
Missing human checks
Actions that should require review can become automatic if nobody writes the boundary down.
No reliable trail
The system may claim success without proving what was checked, denied, approved, or logged.
Axiom generates the checks before risky code runs.
Axiom gives a project a local contract and turns it into concrete artifacts: policy evaluators, route gates, approval payload checks, broker guards, audit requirements, and tests developers can wire into the app.
Human sets the intent
The team describes the app, sensitive data, allowed actions, approvals, and deny paths.
Axiom generates guardrails
The contract becomes deterministic checks, runtime guards, route skeletons, and tests.
App code enforces the decision
The model can draft an action, but generated policy code decides allow, deny, or approval.
What Axiom turns into code
The first layer is readable enough for a human to inspect. The developer layer is generated enough for ordinary software to test and enforce.
What the software should do
Capture the purpose before implementation details and model assumptions take over.
What agents can touch
Name sensitive data, external tools, allowed destinations, and blocked behavior.
What needs approval
Make human approval explicit for risky, irreversible, regulated, or customer-facing actions.
One foundation. Different paths.
Axiom OS is available now as an experimental developer tool. Enterprise and Government are future directions for teams that need stronger governance, reporting, audit, and deployment controls.
Axiom OS
The open-source foundation for AI-assisted apps. Use it locally to define contracts, validate rules, simulate policy behavior, and generate enforcement artifacts.
Explore Axiom OSEnterprise
A planned path for teams adopting AI-assisted development across projects: policy profiles, approval workflows, reporting, and operational controls.
View directionGovernment
A planned path for regulated and public-sector environments: stricter traceability, evidence reporting, deployment verification, and private use.
View directionWhat works today
Axiom OS can initialize starter projects, guide a contract outline, validate `app.ax`, simulate policy behavior, generate TypeScript and Python artifacts, generate policy tests, verify generated files, and run small examples.
What it is not yet
It does not make LLMs obedient, generate a full production application, replace framework code, enforce every runtime request, or guarantee security by itself. It is a foundation for wiring deterministic guardrails into AI-assisted development.
Axiom itself does not spend LLM tokens.
Axiom is a local CLI and generator. Token use only appears when a human or coding agent chooses to put Axiom content into a model context window. The intended workflow is compact commands, targeted simulations, diffs, generated tests, and short summaries, not dumping contracts or generated files into chat.
For builders, it stays concrete.
The public story starts in plain English, but the proof is local and runnable: generated policy evaluators, route gates, approval checks, audit contracts, tests, and verification reports.
$ axiom init $ axiom doctor $ axiom next $ axiom simulate-examples $ axiom generate app.ax --target typescript Result: checked contracts, policy artifacts, tests, guards, and reports a coding agent can use.