# How To: Use Agent Profiles Efficiently

Agent Profiles control how your coding agents behave in different contexts.\
They define what the agent can read, plan, or execute — and how much autonomy it has.

To show how profiles change workflow, we’ll build an NFL Predictor App using two profiles:

* Strategic Agent
* YOLO Agent

{% embed url="<https://youtu.be/iD0R-8fY-tY?si=roCh6d78AuENAyFt>" %}

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### Strategic Agent

Base Model: GPT-5\
Planning Model: Claude 4 Opus

Configuration:

* Apply code diffs → *agent decides*
* Read files → *always allow*
* Create plans → *always allow*
* Execute commands → *ask first*

When run:

1. The agent asks clarifying questions (e.g., *Do you want to scrape players and schedules?*)
2. Builds a detailed 14-step plan
3. Requests user input for environment variables

It’s thorough and safe — but pauses often if you miss setup details.

***

### YOLO Agent

Configuration:

* Apply code diffs → *always allow*
* Read files → *always allow*
* Create plans → *never*
* Execute commands → *always allow*

This agent skips long planning.\
It builds the project quickly, skipping over optional validation and focusing on essentials:

* Data ingestion
* Player stats
* Scoring calculation

It avoids brittle endpoints and produces a working dataset fast — though with fewer checks.

***

### Comparing the Two

| Trait     | Strategic Agent     | YOLO Agent         |
| --------- | ------------------- | ------------------ |
| Planning  | Detailed (14 steps) | Minimal (10 steps) |
| Safety    | High                | Low                |
| Speed     | Moderate            | Very fast          |
| Ideal For | Production projects | Quick prototypes   |