This repository provides a workshop designed to help organizations build teams capable of leveraging AI/ML, including generative AI, for product growth. It targets product managers, developers, and researchers, enabling them to establish cross-functional teams and achieve initial results within 1-3 months by applying Amazon's development processes.

How It Works

The workshop guides participants through a two-part program, preceded by a "Day 0" to clarify roles. Part 1 involves practicing Amazon's development processes, emphasizing a "Working Backwards" approach from customer experience. Part 2 focuses on participant-led re-evaluation of key processes and planning for tangible outcomes within a short timeframe, facilitating rapid hypothesis validation.

Quick Start & Requirements

• Installation: No explicit installation instructions are provided; the content is designed for workshop facilitation.
• Prerequisites: Access to workshop materials (linked within the README) and potentially AWS services for implementation post-workshop.
• Resources: Facilitator guides and presentation materials are available. Links to customer case studies, event videos, and related books are provided for deeper understanding.

Highlighted Details

• Incorporates Amazon's "Working Backwards" methodology for customer-centric product development.
• Features case studies from companies like MUFG, Money Forward, and Genie, showcasing successful AI/ML adoption and business outcomes.
• Offers supplementary materials, including community workshops focused on generative AI use cases and hands-on labs for ML model development.
• Provides guidance on implementing identified use cases using AWS services like Amazon Bedrock and Amazon SageMaker.

Maintenance & Community

• Developed and maintained by AWS, incorporating best practices from Amazon, Spotify, and Uber.
• Feedback and contributions are welcomed via GitHub Issues and Discussions.

Licensing & Compatibility

• Released under the MIT-0 License, allowing free use within the license scope.
• Prohibits the use of the "ML Enablement Workshop" name or similar by third parties to avoid customer confusion.

Limitations & Caveats

The workshop is designed for action planning, not general training, and requires selecting a specific product or feature for focus. While AWS services are recommended for post-workshop implementation, their direct integration within the workshop materials is not the primary focus.