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  • React
  • Angular
  • Vue
  • Svelte
  • NextJS
  • Redux
  • Apollo
  • Storybook
  • D3
  • Testing Library
  • JavaScript
  • TypeScript
  • Node.js
  • Deno
  • Rust
  • Python
  • GraphQL
NEW

How to Use Jev with LangChain for Fast Agent Safety Checks and Typed Decisions

Watch: Jev in an agent loop by Sam Witteveen TypeSafe positions Jev as a System One model. Instead of generating text token by token the way a general LLM does, it accepts unstructured program state plus a list of typed questions, and it returns typed answers with calibrated probabilities in one…
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NEW

Generate a production‑ready Flutter button with Cursor v0 prompts

The short version: before Cursor v0 can help you build a Flutter button that wires in AI analytics, your editor setup often needs to understand Dart. In practice, that means a working Flutter SDK, the right extensions, and a small scaffold project for the agent to target. Get this foundation right…
Thumbnail Image of Tutorial Generate a production‑ready Flutter button with Cursor v0 prompts

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NEW

Choose Cursor CLI over GUI for faster LLM app builds

Terminal AI coding tools can support multiple model providers in a single workflow, while some competing tools are built around one vendor’s stack. Starting a fresh CLI conversation for each task can reduce the context drift that builds up in long GUI threads as visual state, open files, and…
Thumbnail Image of Tutorial Choose Cursor CLI over GUI for faster LLM app builds
NEW

Python-dotenv for RAG Apps: Manage OpenAI, Anthropic, and Vector DB Keys Safely

Put every provider key in one .env file. Call load_dotenv before any RAG component starts. A RAG app may query OpenAI, call Anthropic, and store vectors in Pinecone. That means at least three API keys before retrieval logic begins. Hardcoding them works until a GitHub push exposes every credential.…
Thumbnail Image of Tutorial Python-dotenv for RAG Apps: Manage OpenAI, Anthropic, and Vector DB Keys Safely
NEW

Rust AI Apps with Rig: Connect Ollama, RAG, and Tool Calls

A RAG service (retrieval-augmented generation, where the model answers from your own documents) built with Rust and Rig can have a much smaller runtime memory footprint than an equivalent Python LangChain server in many local-serving setups. Rust’s lack of garbage-collection pauses can also help…
Thumbnail Image of Tutorial Rust AI Apps with Rig: Connect Ollama, RAG, and Tool Calls