Manage your schedule and events without leaving your workspace.

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Tuturuuu Docs

Welcome to the home of Tuturuuu Documentation.

Introduction

Development

Understanding Tuturuuu monorepo architecture and the benefits of using Turborepo.

Monorepo Architecture

Learn how Tuturuuu uses Conventional Commits and Branch naming to improve development workflow.

Git Conventions

Learn how to work with Supabase locally in the Tuturuuu development workflow.

Local Supabase Development

Understanding Tuturuuu CI/CD pipelines and automated workflows.

CI/CD Pipelines

Learn how to contribute to our documentation.

Documenting

Meet Together helps you to find the best time to meet with everyone.

Meet Together

Learn how to use Vercel AI SDK for structured data generation in Tuturuuu.

AI Structured Data

Themes

Language

Build forms with ease, integrated with all Tuturuuu services.

Form Builder

Manage your workspace finances with ease.

Finance

Manage tasks and monitor progress without any hassle.

Project Management

Talk to an AI-powered assistant that understands your workspace and helps you get things done, faster and easier.

AI Chat

A foundational guide for NEO LEAGUE: Prompt the Future — empowering students to master the art of prompting and unlock AI’s full creative potential.

Introduction to Prompt Engineering

Master the art of prompt crafting with strategic techniques to guide AI responses, structure output, and enhance clarity.

Prompt Design Strategies

Learn how to design prompts with clear tasks, constraints, and formatting guidance for more accurate AI responses.

Give Clear and Specific Instructions

Explore zero-shot vs few-shot prompting, and how to use examples to teach the model desired output patterns and styles.

Use Few-Shot Examples Effectively

Add background details, references, or brand-specific data to help the model generate more targeted responses.

Include Relevant Context

Use labeled prefixes and incomplete structures to guide the model’s response format and intent.

Guide with Prefixes and Partial Patterns

Simplify complex tasks using modular instructions, chaining prompts step-by-step, or aggregating outputs.

Break Down Prompts into Manageable Parts

Understand temperature, top-p, and max token settings. Learn how to refine your prompt through experimentation.

Tune Parameters and Iterate on Prompts

Handle fallback messages and understand the model’s limitations with factual content, logic, and math.

Get Started

Features

AI Features

Personalization

Experiments

Prompt Engineering

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