Explorar skills

Value-based pricing framework with Van Westendorp PSM analysis. Designs tier structure, packaging strategy, and unit economics. Produces comprehensive pricing strategy with Good-Better-Best model, competitive positioning, and implementation roadmap.

OKR-driven 18-month strategic roadmap with milestone-based execution plan. Transforms strategy into actionable phases with clear success metrics and resource allocation.

Comprehensive brand identity system including brand strategy, visual identity (colors, typography, logo direction), messaging architecture (taglines, boilerplates), and tone of voice guidelines with before/after examples and implementation roadmap.

Comprehensive community building strategy including platform selection, channel structure, member journey mapping, engagement ladder tactics, community programming rituals, moderation guidelines, launch plan, growth strategy, and success metrics for building thriving online communities

Comprehensive content marketing strategy including content pillars, 90-day editorial calendar, distribution strategy, SEO optimization, and repurposing playbook using Content Pillars, Hub-and-Spoke, and 10x Content frameworks.

Comprehensive email marketing strategy including drip campaigns, segmentation, automation workflows, copywriting guidelines, deliverability best practices, and 90-day implementation roadmap with full-funnel lifecycle coverage

Comprehensive metrics dashboard strategy including North Star Metric definition, AARRR Pirate Metrics framework, product engagement tracking, 5 role-specific dashboards, alert configuration, data infrastructure planning, and 90-day implementation roadmap for data-driven decision making

Create and manage data loading, preprocessing, and augmentation pipelines (DataModule, transforms, data loaders). Use when implementing DataModules, setting up data loaders, or optimizing data pipelines for computer vision, NLP, or graph ML tasks.

Format Python code with ruff formatter and optionally fix auto-fixable linting issues. Use when formatting code, preparing code for commit, or ensuring consistent code style across the project.

Comprehensive guide for Hydra configuration management, hierarchical configs, experiment management, Optuna integration, and Lightning integration patterns

Export trained PyTorch models to various formats (ONNX, TorchScript, TensorRT) and upload to model registries (Hugging Face Hub, MLflow). Use when deploying models, sharing trained weights, or preparing for production inference.

Comprehensive validation of ML project structure, configurations, code quality, and training readiness. Use when setting up a new project, before training runs, or debugging configuration issues. Validates config loading, data pipeline, model architecture, and dependencies.