> ## Documentation Index
> Fetch the complete documentation index at: https://docs.a1project.org/llms.txt
> Use this file to discover all available pages before exploring further.

# Quick Start

> Get up and running with A1 in 5 minutes.

## Your First Agent

```bash theme={null}
pip install a1-compiler
```

```python theme={null}
from a1 import Agent, tool, LLM
from pydantic import BaseModel

# Define a tool
@tool(name="add", description="Add two numbers")
async def add(a: int, b: int) -> int:
    return a + b

# Define schemas
class MathInput(BaseModel):
    problem: str

class MathOutput(BaseModel):
    answer: int

# Create an agent
agent = Agent(
    name="math_agent",
    description="Solves simple math problems",
    input_schema=MathInput,
    output_schema=MathOutput,
    tools=[add, LLM(model="gpt-4.1")],
)

async def main():
    # Compile ahead-of-time
    compiled = await agent.aot(
      strategy=Strategy(
        generate=BaseGenerate(
          llm_tool=LLM(model="gpt-4.1"),
        )
      )
    )
    result = await compiled.execute(problem="What is 2 + 2?")
    print(f"AOT result: {result}")

    # Or execute just-in-time
    result = await agent.jit(problem="What is 5 + 3?")
    print(f"JIT result: {result}")

import asyncio
asyncio.run(main())
```

## Key Concepts

1. **Tools** - Functions that agents can call.
2. **Agent** - A composition of tools with input/output schemas.
3. **Compilation** - AOT (ahead-of-time) or JIT (just-in-time) modes.
4. **Schemas** - Pydantic models for type-safe input/output.

## Next Steps

* Learn about [Agents](../guide/agents.md)
* Explore [Tools](../guide/tools.md)
* Understand [Core Concepts](concepts.md)