Building an Agent Lab with Guardrails

Agent experiments were useful, but each prototype had its own shape and its own failure patterns.

Agent prototypes were hard to compare because each one behaved differently and lacked a shared evaluation shape.

• Keep runtime complexity low
• Log enough context to compare failures
• Avoid treating experimental loops as production systems

1. Split the lab into small experiments.
2. Logged prompts, outputs, and failure modes.
3. Added quality checks for each workflow path.
4. Kept the runtime intentionally simple.

Used a narrow content model and testable workflow boundaries so experiments could be compared without guesswork.

• Evaluation shape should be designed before the agent loop grows.
• Simple traces beat clever abstractions in early experiments.