Skip to content
#

best-practices

Here are 190 public repositories matching this topic...

Collective Knowledge (CK), Collective Mind (CM/CMX) and MLPerf automations: community-driven projects to facilitate collaborative and reproducible research and to learn how to run AI, ML, and other emerging workloads more efficiently and cost-effectively across diverse models, datasets, software, and hardware using MLPerf methodology and benchmarks

  • Updated Sep 13, 2025
  • Python

This methodology provides a structured approach for collaborating with AI systems on software development projects. It addresses common issues like code bloat, architectural drift, and context dilution through systematic constraints and validation checkpoints.

  • Updated Sep 17, 2025
  • Python

A comprehensive collection of AI development patterns for building software with AI assistance, organized by implementation maturity and development lifecycle phases. Includes Foundation, Development, and Operations patterns with practical examples and anti-patterns.

  • Updated Nov 19, 2025
  • Python
tomodachi

💻 Microservice lib designed to ease service building using Python and asyncio, with ready to use support for HTTP + WS, AWS SNS+SQS, RabbitMQ / AMQP, middlewares, envelopes, logging, lifecycles. Extend to GraphQL, protobuf, etc.

  • Updated Mar 11, 2025
  • Python

Improve this page

Add a description, image, and links to the best-practices topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the best-practices topic, visit your repo's landing page and select "manage topics."

Learn more