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

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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.

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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.

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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