Growth Engine

Growth Engine

Autonomous growth experimentation framework based on Karpathy's autoresearch pattern applied to marketing. Creates experiments with hypotheses, logs data points, runs statistical analysis (bootstrap CI + Mann-Whitney U), auto-promotes winners to a living playbook, and suggests next experiments. Supports batch mode (up to 10 variants simultaneously).

Usage

Use this skill when:

• Creating or managing A/B or multivariate experiments for any marketing channel
• Logging experiment data points after content is published or campaigns run
• Scoring experiments to determine statistical winners
• Checking the playbook for proven best practices before creating new content
• Generating weekly scorecards across all channels
• Monitoring campaign pacing and health

Do NOT use for:

• One-off content creation (use the playbook output as input, but don't run the engine)
• Non-experiment analytics or reporting
• Campaign setup in external platforms (this tracks experiments, not campaign config)

Commands

Create an experiment

python3 experiment-engine.py create \
  --agent <agent_name> \
  --hypothesis "What you expect to happen" \
  --variable "<variable_name>" \
  --variants '["variant_a", "variant_b"]' \
  --metric "<primary_metric>" \
  --cycle-hours 24

Add --batch-mode for 3-10 variant tests. Add --min-samples N to override auto-detection.

Log a data point

python3 experiment-engine.py log \
  --agent <agent_name> \
  --experiment-id <EXP-ID> \
  --variant "<variant_name>" \