Tesla Gateway is a reference implementation that demonstrates how an AI system can operate through a governed agentic loop:
Observe → Decide → Act → Verify
using a Tesla vehicle as a familiar real-world example of stateful systems and APIs.
This is not voice commands.
This is not autonomous control.
This is not a product.This is an agentic loop, implemented safely and explicitly.
A minimal FastAPI gateway service that accepts human intent and determines:
- what state to observe
- what actions (if any) are appropriate
- whether those actions are allowed
- how to verify the outcome
Example intent:
“I’m heading out in 10 minutes.”
The system:
- Observes current system state
- Decides what needs to change
- Executes only explicitly allowed actions
- Verifies the resulting state
No commands are issued.
Only intent is provided.
This repository contains the open-core reference implementation, including:
- the governed observe → decide → act → verify loop
- the decision engine
- the governance and safety model
- a MockProvider for simulation and learning
- deterministic, inspectable outputs
It is intentionally provider-agnostic.
- ❌ Tesla Fleet authentication
- ❌ OAuth / token refresh logic
- ❌ Vehicle pairing or wake transports
- ❌ Live Tesla API execution
- ❌ Private keys, secrets, or credentials
Those components live in a private adapter repository and are excluded by design.
This boundary is intentional.
- ❌ Not voice control
- ❌ Not full vehicle automation
- ❌ Not autonomous driving
- ❌ Not a production system
- ❌ Not a consumer product
Tesla Gateway exists to teach and prove the agentic loop, not to replace Tesla software.
Tesla is familiar — and that’s intentional.
The vehicle is not the product.
It’s the proof.
If an agentic loop can:
- safely observe
- reason about intent
- act within constraints
- verify outcomes
on a real-world system like a car, the same pattern applies to:
- desktops
- smart homes
- cloud infrastructure
- network operations
Tesla Gateway is the consumer-domain proof of the AIMusubi platform.
This implementation is governed by design:
- Explicit intent — nothing happens without a clear user goal
- Action allowlists — only permitted actions can execute
- Confirmation gates — sensitive actions require confirmation
- Simulation-first — no live execution by default
- Verify step — state is always re-checked after action
The agent does not “decide freely.”
It operates within declared constraints.
Human Intent
→ API Endpoint
→ Observe (provider state)
→ Decide (decision engine)
→ Act (scoped provider actions)
→ Verify (re-observe state)
Every step is visible.
Nothing is hidden.
Everything is inspectable.
- Uses the included MockProvider
- No external APIs
- No credentials required
- Deterministic, safe behavior
- Ideal for learning and experimentation
Live execution is supported in principle by the architecture,
but real Tesla execution is not included in this repository.
Private adapters can implement the same provider interface for controlled personal use.
POST /intent/prepare_departure?vehicle_alias=modelx
Returns:
- Observed state (before)
- Actions selected
- Action results (dry-run by default)
- Verified state (after)
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
uvicorn app.main:app --reload