development

China Unicom's Yuanjing Wanwu Agent Platform is an enterprise-grade, multi-tenant AI agent development platform. It helps users build applications such as intelligent agents, workflows, and rag, and also supports model management. The platform features a developer-friendly license, and we welcome all developers to build upon the platform.

UME is an in-app debug kits platform for Flutter. Produced by Flutter Infra team of ByteDance

Open-core workflow engine powering Bubble Lab — and fully runnable, hostable, and extensible on its own.

Flow-Like: Strongly Typed Enterprise Scale Workflows. Built for scalability, speed, seamless AI integration and rich customization.

Code research platform for AI agents; find, understand, and prove context across your code and all of GitHub, in a fraction of the tokens. One toolset, MCP or CLI

Nylo is the fastest way to build your next Flutter mobile app. Streamline your projects with Nylo's opinionated approach to building Flutter apps. Develop your next idea ⚡️

Prompt Driven Development (PDD): The Last Programming Language™. Prompt files are source; code is generated output.

[DEPRECATED] Powered by AI Playgrounds by E2B. Code interpreter on steroids for ChatGPT. Run any language, any terminal process, use filesystem freely. All with access to the internet.

This document is a compilation of best practices for AI-Native development, curated by our community. Discover useful tips and tricks for leveraging tools to improve your AI development process.

Autonomous Engineering

FACET (Feature‑Aware Contracted Extension for Text) is a human‑readable, machine‑deterministic markup language for AI prompting, orchestration, and tooling

A workflow execution platform built on top of the fantastic Cloudflare infrastructure.

A curated, hands-on library of notebooks, demos, and resources for AI/ML, Deep Learning, Generative AI, AI-Agents, fine-tuning, and modern tooling.

Production-grade AI evaluation, prompt management & observability SDK. Automated evaluations with sub-100ms guardrails. No human-in-the-loop required. Python + TypeScript.

🤫 Token-lean sessions at the harness level. An easy to grasp output style, output-shrinking hooks, and log compression cut both input and output tokens.