diff --git a/01_getting_started/01_hello_world/README.md b/01_getting_started/01_hello_world/README.md
index b75d0dc..a72e3b0 100644
--- a/01_getting_started/01_hello_world/README.md
+++ b/01_getting_started/01_hello_world/README.md
@@ -7,23 +7,21 @@ Simple example demonstrating GPU-based serverless workers with automatic scaling
 ### 1. Install Dependencies
 
 ```bash
-pip install -r requirements.txt
+uv sync
 ```
 
-### 2. Configure Environment
-
-Create `.env` file:
+### 2. Authenticate
 
 ```bash
-RUNPOD_API_KEY=your_api_key_here
+uv run flash login
 ```
 
-Get your API key from [Runpod Settings](https://www.runpod.io/console/user/settings).
+Or create a `.env` file with `RUNPOD_API_KEY=your_api_key_here`.
 
 ### 3. Run Locally
 
 ```bash
-flash run
+uv run flash run
 ```
 
 Server starts at **http://localhost:8888**
diff --git a/01_getting_started/02_cpu_worker/README.md b/01_getting_started/02_cpu_worker/README.md
index a242690..4d5fb88 100644
--- a/01_getting_started/02_cpu_worker/README.md
+++ b/01_getting_started/02_cpu_worker/README.md
@@ -7,23 +7,21 @@ Simple example demonstrating CPU-based serverless workers with automatic scaling
 ### 1. Install Dependencies
 
 ```bash
-pip install -r requirements.txt
+uv sync
 ```
 
-### 2. Configure Environment
-
-Create `.env` file:
+### 2. Authenticate
 
 ```bash
-RUNPOD_API_KEY=your_api_key_here
+uv run flash login
 ```
 
-Get your API key from [Runpod Settings](https://www.runpod.io/console/user/settings).
+Or create a `.env` file with `RUNPOD_API_KEY=your_api_key_here`.
 
 ### 3. Run Locally
 
 ```bash
-flash run
+uv run flash run
 ```
 
 Server starts at **http://localhost:8888**
diff --git a/01_getting_started/03_mixed_workers/README.md b/01_getting_started/03_mixed_workers/README.md
index ae466af..78e8562 100644
--- a/01_getting_started/03_mixed_workers/README.md
+++ b/01_getting_started/03_mixed_workers/README.md
@@ -53,15 +53,14 @@ If you haven't run the repository-wide setup:
 
 ```bash
 # Install dependencies
-pip install -r requirements.txt
+uv sync
 
-# Set API key (choose one):
-export RUNPOD_API_KEY=your_api_key_here
-# OR create .env file:
-echo "RUNPOD_API_KEY=your_api_key_here" > .env
+# Authenticate
+uv run flash login
+# Or create .env file with RUNPOD_API_KEY=your_api_key_here
 
 # Run
-flash run
+uv run flash run
 ```
 
 Server starts at http://localhost:8888
diff --git a/01_getting_started/04_dependencies/README.md b/01_getting_started/04_dependencies/README.md
index d3f251e..5ea27fe 100644
--- a/01_getting_started/04_dependencies/README.md
+++ b/01_getting_started/04_dependencies/README.md
@@ -28,15 +28,14 @@ If you haven't run the repository-wide setup:
 
 ```bash
 # Install dependencies
-pip install -r requirements.txt
+uv sync
 
-# Set API key (choose one):
-export RUNPOD_API_KEY=your_api_key_here
-# OR create .env file:
-echo "RUNPOD_API_KEY=your_api_key_here" > .env
+# Authenticate
+uv run flash login
+# Or create .env file with RUNPOD_API_KEY=your_api_key_here
 
 # Run
-flash run
+uv run flash run
 ```
 
 ## Dependency Types
diff --git a/01_getting_started/README.md b/01_getting_started/README.md
index 8b20778..4a18ac3 100644
--- a/01_getting_started/README.md
+++ b/01_getting_started/README.md
@@ -60,8 +60,8 @@ Managing Python packages and system dependencies.
 
 1. Start with **01_hello_world** to understand the basics
 2. Explore **03_mixed_workers** for cost optimization and validation patterns
-3. Move to **02_cpu_worker** to learn CPU-only patterns _(coming soon)_
-4. Master **04_dependencies** for production readiness _(coming soon)_
+3. Move to **02_cpu_worker** to learn CPU-only patterns
+4. Master **04_dependencies** for production readiness
 
 ## Next Steps
 
diff --git a/02_ml_inference/01_text_to_speech/README.md b/02_ml_inference/01_text_to_speech/README.md
index 30be7bd..4b89a47 100644
--- a/02_ml_inference/01_text_to_speech/README.md
+++ b/02_ml_inference/01_text_to_speech/README.md
@@ -24,15 +24,16 @@ This example demonstrates running a 1.7B parameter TTS model on serverless GPU i
 
 ```bash
 cd 02_ml_inference/01_text_to_speech
-pip install -r requirements.txt
-cp .env.example .env
-# Add your RUNPOD_API_KEY to .env
+uv sync
+uv run flash login
 ```
 
+Or create a `.env` file with `RUNPOD_API_KEY=your_api_key_here`.
+
 ### Run
 
 ```bash
-flash run
+uv run flash run
 ```
 
 First run provisions the endpoint (~1 min). Server starts at http://localhost:8888
diff --git a/02_ml_inference/README.md b/02_ml_inference/README.md
index cd41fed..be41df1 100644
--- a/02_ml_inference/README.md
+++ b/02_ml_inference/README.md
@@ -4,6 +4,15 @@ Deploy machine learning models as production-ready APIs. Learn how to serve LLMs
 
 ## Examples
 
+### [01_text_to_speech](./01_text_to_speech/)
+Text-to-Speech API using Qwen3-TTS.
+
+**What you'll learn:**
+- Running HuggingFace models with `@remote` on GPU workers
+- Returning binary audio data (WAV) from API endpoints
+- Using `bfloat16` precision for memory-efficient inference
+- Input validation inside self-contained `@remote` functions
+
 ### 01_text_generation _(coming soon)_
 LLM inference API with streaming support.
 
diff --git a/03_advanced_workers/05_load_balancer/README.md b/03_advanced_workers/05_load_balancer/README.md
index c3f45d7..f3071ac 100644
--- a/03_advanced_workers/05_load_balancer/README.md
+++ b/03_advanced_workers/05_load_balancer/README.md
@@ -26,22 +26,21 @@ Load-balanced endpoints use direct HTTP routing to serverless workers, providing
 ### 1. Install Dependencies
 
 ```bash
-pip install -r requirements.txt
+uv sync
 ```
 
-### 2. Configure Environment
+### 2. Authenticate
 
 ```bash
-cp .env.example .env
-# Add your RUNPOD_API_KEY to .env
+uv run flash login
 ```
 
-Get your API key from [Runpod Settings](https://www.runpod.io/console/user/settings).
+Or create a `.env` file with `RUNPOD_API_KEY=your_api_key_here`.
 
 ### 3. Run Locally (from repository root)
 
 ```bash
-flash run
+uv run flash run
 ```
 
 Visit **http://localhost:8888/docs** for interactive API documentation (unified app with all examples).
diff --git a/04_scaling_performance/01_autoscaling/README.md b/04_scaling_performance/01_autoscaling/README.md
index ddb76de..2d8101a 100644
--- a/04_scaling_performance/01_autoscaling/README.md
+++ b/04_scaling_performance/01_autoscaling/README.md
@@ -4,7 +4,7 @@ Configure Flash worker autoscaling for different workload patterns. This example
 
 ## Quick Start
 
-**Prerequisites**: Complete the [repository setup](../../README.md#quick-start) first (clone, `make dev`, set API key).
+**Prerequisites**: Complete the [repository setup](../../README.md#quick-start) first, or run `flash login` to authenticate.
 
 ```bash
 cd 04_scaling_performance/01_autoscaling
diff --git a/05_data_workflows/01_network_volumes/README.md b/05_data_workflows/01_network_volumes/README.md
index d8d325c..bd9cf24 100644
--- a/05_data_workflows/01_network_volumes/README.md
+++ b/05_data_workflows/01_network_volumes/README.md
@@ -11,23 +11,21 @@ The GPU worker generates images with Stable Diffusion and writes them to a Runpo
 ### 1. Install Dependencies
 
 ```bash
-pip install -r requirements.txt
+uv sync
 ```
 
-### 2. Configure Environment
-
-Create `.env`:
+### 2. Authenticate
 
 ```bash
-RUNPOD_API_KEY=your_api_key_here
+uv run flash login
 ```
 
-Get your API key from [Runpod Settings](https://www.runpod.io/console/user/settings).
+Or create a `.env` file with `RUNPOD_API_KEY=your_api_key_here`.
 
 ### 3. Run Locally
 
 ```bash
-flash run
+uv run flash run
 ```
 
 Server starts at `http://localhost:8888`
diff --git a/05_data_workflows/README.md b/05_data_workflows/README.md
index 7b1623b..87be705 100644
--- a/05_data_workflows/README.md
+++ b/05_data_workflows/README.md
@@ -4,7 +4,7 @@ Handle data storage, processing, and pipelines in Flash applications. Learn pers
 
 ## Examples
 
-### 01_network_volumes _(coming soon)_
+### [01_network_volumes](./01_network_volumes/)
 Persistent storage with Runpod network volumes.
 
 **What you'll learn:**
diff --git a/CLI-REFERENCE.md b/CLI-REFERENCE.md
index a058cf3..142beba 100644
--- a/CLI-REFERENCE.md
+++ b/CLI-REFERENCE.md
@@ -21,6 +21,7 @@ flash <command> --help    # Show help for specific command
 
 | Command | Purpose |
 |---------|---------|
+| [`flash login`](#flash-login) | Authenticate with Runpod |
 | [`flash init`](#flash-init) | Create new Flash project |
 | [`flash run`](#flash-run) | Run development server |
 | [`flash build`](#flash-build) | Build application package |
@@ -60,6 +61,51 @@ flash <command> --help    # Show help for specific command
 
 ---
 
+## flash login
+
+Authenticate with Runpod. Opens a browser for authentication and saves credentials locally.
+
+### Syntax
+
+```bash
+flash login
+```
+
+### What It Does
+
+1. Opens your default browser to Runpod's authentication page
+2. After you authenticate, saves credentials securely
+3. Environment variables persist across sessions
+
+### Examples
+
+**Authenticate with Runpod:**
+```bash
+flash login
+# Opens browser for authentication
+```
+
+### Alternative: Manual Configuration
+
+If `flash login` doesn't work in your environment, you can set the API key manually:
+
+```bash
+# Set environment variable
+export RUNPOD_API_KEY=your-key-here
+
+# Or add to .env file
+echo "RUNPOD_API_KEY=your-key-here" > .env
+```
+
+Get your API key from [Runpod Settings](https://www.runpod.io/console/user/settings).
+
+### Related Commands
+
+- [`flash run`](#flash-run) - Run development server (requires authentication)
+- [`flash deploy`](#flash-deploy) - Deploy to Runpod (requires authentication)
+
+---
+
 ## flash init
 
 Create a new Flash project with the correct structure and boilerplate code.
diff --git a/DEVELOPMENT.md b/DEVELOPMENT.md
index 9efc3f5..984e29a 100644
--- a/DEVELOPMENT.md
+++ b/DEVELOPMENT.md
@@ -155,6 +155,45 @@ Virtual Environment: Active (.venv exists)
 Python Version: Python 3.12.10
 ```
 
+### Running Flash with Different Package Managers
+
+After `make setup` completes, you can run Flash in two ways:
+
+**Option A: Using Package Manager Prefix (recommended for uv/poetry/pipenv/conda)**
+
+Run commands with the package manager prefix without activation:
+
+```bash
+# With uv
+uv run flash run
+
+# With poetry
+poetry run flash run
+
+# With pipenv
+pipenv run flash run
+
+# With conda
+conda run -p ./.venv flash run
+```
+
+**Option B: Activate Virtual Environment (works with all managers)**
+
+Alternatively, activate the virtual environment first:
+
+```bash
+# Unix/macOS
+source .venv/bin/activate
+
+# Windows
+.venv\Scripts\activate
+
+# Then run normally
+flash run
+```
+
+Once activated, you can run Flash and other commands directly without a prefix.
+
 ## Makefile Commands
 
 ### Help
@@ -217,6 +256,14 @@ Shows all available commands with your detected environment manager.
 
 The Flash CLI provides commands for local development, building, and deployment.
 
+### Authentication
+
+```bash
+flash login                  # Authenticate with Runpod (opens browser)
+```
+
+Or set `RUNPOD_API_KEY` in your `.env` file.
+
 ### Development Commands
 
 ```bash
@@ -495,6 +542,66 @@ make clean-venv
 make setup
 ```
 
+## Unified App Architecture
+
+The root directory provides a programmatic discovery system that automatically finds and loads all examples when you run `flash run` from the project root.
+
+### Discovery Process
+
+1. Scans all example category directories (`01_getting_started/`, `02_ml_inference/`, etc.)
+2. Detects `@remote` decorated functions in `.py` files via AST parsing
+3. Dynamically generates routes with unique prefixes (e.g., `/01_hello_world/gpu/`)
+4. Generates metadata and documentation automatically
+
+### Benefits
+
+- Add new examples without modifying any central configuration
+- Consistent routing across all examples
+- Single entry point for exploring all functionality
+- Automatic discovery eliminates manual registration
+
+### Example Structure
+
+Each example follows this flat-file pattern:
+
+```
+example_name/
+├── README.md              # Documentation and deployment guide
+├── gpu_worker.py          # @remote decorated functions (GPU)
+├── cpu_worker.py          # @remote decorated functions (CPU, optional)
+├── pyproject.toml         # Project dependencies
+└── .gitignore             # Git ignore patterns
+```
+
+### Example Dependency Syncing
+
+The unified app requires all example dependencies to be installed in the root environment for discovery to work.
+
+**Automatic Dependency Syncing:**
+
+When adding a new example with additional dependencies:
+
+1. Define dependencies in your example's `pyproject.toml`
+2. Run `make sync-example-deps` to update the root dependencies
+3. Run `uv sync --all-groups` (or `make setup`) to install new packages
+4. Run `make requirements.txt` to regenerate the lockfile
+
+The sync script automatically:
+- Scans all example directories for `pyproject.toml` files
+- Merges dependencies into the root configuration
+- Filters out transitive dependencies already provided by `runpod-flash`
+- Detects version conflicts and uses the most permissive constraint
+- Preserves essential root dependencies (numpy, torch, runpod-flash)
+
+**Example:**
+
+```bash
+# After adding a new example with pillow and structlog dependencies
+make sync-example-deps  # Syncs example deps to root pyproject.toml
+uv sync --all-groups    # Installs new dependencies
+make requirements.txt   # Regenerates lockfile
+```
+
 ## Troubleshooting
 
 ### Package Manager Not Detected
diff --git a/README.md b/README.md
index 155773d..b0099f0 100644
--- a/README.md
+++ b/README.md
@@ -4,342 +4,74 @@ A collection of example applications showcasing Runpod Flash - a framework for b
 
 ## What is Flash?
 
-Flash is a CLI tool and framework from the `runpod_flash` package that enables you to build FastAPI applications with workers that run on Runpod's serverless infrastructure. Write your code locally, and Flash handles deployment, scaling, and resource management.
+Flash is a Python framework that lets you run functions on Runpod's Serverless infrastructure with a single decorator. Write code locally, deploy globally—Flash handles provisioning, scaling, and routing automatically.
 
-## Prerequisites
-
-- Python 3.10+ (3.12 recommended)
-- [Runpod Account](https://console.runpod.io/signup)
-- [Runpod API Key](https://docs.runpod.io/get-started/api-keys)
-- Flash CLI: `pip install runpod_flash`
-
-## Quick Start
-
-```bash
-# Clone the repository
-git clone https://github.com/runpod/flash-examples.git
-cd flash-examples
-
-# Setup development environment (auto-detects package manager)
-make setup
-
-# The setup will:
-# - Create virtual environment
-# - Install all dependencies
-# - Create .env file from template
-# - Verify your setup
-
-# Add your API key to .env file
-# Get your key from: https://www.runpod.io/console/user/settings
-nano .env  # or use your preferred editor
-
-# Run all examples from the unified app (recommended)
-flash run
-
-# Visit http://localhost:8888/docs
-```
+```python
+from runpod_flash import Endpoint, GpuType
 
-**Verification:**
-After setup, verify your environment is correct:
-```bash
-make verify-setup
+@Endpoint(name="image-gen", gpu=GpuType.NVIDIA_GEFORCE_RTX_4090, dependencies=["torch", "diffusers"])
+async def generate_image(prompt: str) -> bytes:
+    # This runs on a cloud GPU, not your laptop
+    ...
 ```
 
-This checks:
-- Python version (3.10+ required)
-- Virtual environment exists
-- Flash CLI is installed
-- API key is configured
+**Key features:**
+- **`@Endpoint` decorator**: Mark any async function to run on serverless infrastructure
+- **Auto-scaling**: Scale to zero when idle, scale up under load
+- **Local development**: `flash run` starts a local server with hot reload
+- **One-command deploy**: `flash deploy` packages and ships your code
 
-**Alternative Setup Methods:**
-- **With Makefile**: `make setup` (auto-detects your package manager)
-- **With uv**: `uv sync && uv pip install -e .`
-- **With pip**: `pip install -e .`
-- **With poetry**: `poetry install`
-
-**Using Different Package Managers:**
+## Prerequisites
 
-The setup automatically detects and uses your available package manager in this order:
-1. uv
-2. poetry
-3. pipenv
-4. pip (standard Python package manager)
-5. conda
+- **Python 3.10+**
+- **uv**: Install with `curl -LsSf https://astral.sh/uv/install.sh | sh`
+- **Runpod account**: [Sign up here](https://runpod.io/console/signup)
 
-To explicitly use a specific package manager:
+## Quick Start
 
 ```bash
-# Force pip usage
-PKG_MANAGER=pip make setup
-
-# Force poetry
-PKG_MANAGER=poetry make setup
-
-# Force conda
-PKG_MANAGER=conda make setup
-```
-
-**Running Flash Examples:**
-
-After `make setup` completes, you can run Flash in two ways:
-
-**Option A: Using Package Manager Prefix (recommended for uv/poetry/pipenv/conda)**
+# Clone and install
+git clone https://github.com/runpod/flash-examples.git
+cd flash-examples
+uv sync && uv pip install -e .
 
-With uv, poetry, pipenv, or conda, run commands with the package manager prefix without activation:
+# Authenticate with Runpod
+uv run flash login
 
-```bash
-# With uv
+# Run all examples locally
 uv run flash run
-
-# With poetry
-poetry run flash run
-
-# With pipenv
-pipenv run flash run
-
-# With conda
-conda run -p ./.venv flash run
-```
-
-**Option B: Activate Virtual Environment (works with all managers)**
-
-Alternatively, activate the virtual environment first:
-
-```bash
-# Unix/macOS
-source .venv/bin/activate
-
-# Windows
-.venv\Scripts\activate
-
-# Then run normally
-flash run
 ```
 
-Once activated, you can run Flash and other commands directly without a prefix.
-
-**Note**: After running `make setup`, all example dependencies are installed. You can navigate to any example directory and run `flash run` immediately. The `make setup` command will show you the recommended next steps based on your detected package manager.
-
-For detailed development instructions, see [DEVELOPMENT.md](./DEVELOPMENT.md).
-
-## Examples by Category
-
-### 01 - Getting Started
-Learn the fundamentals of Flash applications.
+Open **http://localhost:8888/docs** to explore all endpoints.
 
-- **[01_hello_world](./01_getting_started/01_hello_world/)** - The simplest Flash application with GPU workers
-- **[02_cpu_worker](./01_getting_started/02_cpu_worker/)** - CPU-only worker example
-- **[03_mixed_workers](./01_getting_started/03_mixed_workers/)** - Mixed GPU/CPU workers with cost optimization and validation
-- **[04_dependencies](./01_getting_started/04_dependencies/)** - Managing Python and system dependencies
+> **Using pip, poetry, or conda?** See [DEVELOPMENT.md](./DEVELOPMENT.md) for alternative setups.
 
-### 02 - ML Inference
-Deploy machine learning models as APIs.
+## Examples
 
-- 01_text_generation - LLM inference (Llama, Mistral, etc.) _(coming soon)_
-- 02_image_generation - Stable Diffusion image generation _(coming soon)_
-- 03_embeddings - Text embeddings API _(coming soon)_
-- 04_multimodal - Vision-language models _(coming soon)_
+| Category | Example | Description |
+|----------|---------|-------------|
+| **Getting Started** | [01_hello_world](./01_getting_started/01_hello_world/) | Basic GPU worker |
+| | [02_cpu_worker](./01_getting_started/02_cpu_worker/) | CPU-only worker |
+| | [03_mixed_workers](./01_getting_started/03_mixed_workers/) | GPU + CPU pipeline |
+| | [04_dependencies](./01_getting_started/04_dependencies/) | Dependency management |
+| **ML Inference** | [01_text_to_speech](./02_ml_inference/01_text_to_speech/) | Qwen3-TTS model serving |
+| **Advanced** | [05_load_balancer](./03_advanced_workers/05_load_balancer/) | HTTP routing with load balancer |
+| **Scaling** | [01_autoscaling](./04_scaling_performance/01_autoscaling/) | Worker autoscaling configuration |
+| **Data** | [01_network_volumes](./05_data_workflows/01_network_volumes/) | Persistent storage with network volumes |
 
-### 03 - Advanced Workers
-Production-ready worker patterns.
+More examples coming soon in each category.
 
-- 01_streaming - Streaming responses (SSE/WebSocket) _(coming soon)_
-- 02_batch_processing - Batch inference optimization _(coming soon)_
-- 03_caching - Model and result caching strategies _(coming soon)_
-- 04_custom_images - Custom Docker images _(coming soon)_
-- **[05_load_balancer](./03_advanced_workers/05_load_balancer/)** - Load-balancer endpoints with custom HTTP routes
-
-### 04 - Scaling & Performance
-Optimize for production workloads.
-
-- 01_autoscaling - Worker autoscaling configuration _(coming soon)_
-- 02_gpu_optimization - GPU memory management _(coming soon)_
-- 03_concurrency - Async patterns and concurrency _(coming soon)_
-- 04_monitoring - Logging, metrics, and observability _(coming soon)_
-
-### 05 - Data Workflows
-Handle data storage and processing.
-
-- 01_network_volumes - Persistent storage with network volumes _(coming soon)_
-- 02_file_upload - Handling file uploads _(coming soon)_
-- 03_data_pipelines - ETL workflows _(coming soon)_
-- 04_s3_integration - Cloud storage integration _(coming soon)_
-
-### 06 - Real World Applications
-Complete production-ready applications.
-
-- 01_chatbot_api - Production chatbot service _(coming soon)_
-- 02_image_api - Image processing service _(coming soon)_
-- 03_audio_transcription - Whisper transcription service _(coming soon)_
-- 04_multimodel_pipeline - Complex multi-stage workflows _(coming soon)_
-
-## Learning Path
-
-**New to Flash?** Start here:
-1. [01_getting_started/01_hello_world](./01_getting_started/01_hello_world/) - Understand the basics
-2. [01_getting_started/03_mixed_workers](./01_getting_started/03_mixed_workers/) - Learn cost optimization and validation patterns
-3. 02_ml_inference/01_text_generation - Deploy your first model
-
-**Coming from Modal?**
-Flash is FastAPI-centric for building production applications, while Modal focuses on standalone functions. Flash provides structured application development with built-in routing and deployment management.
-
-**Production Deployment?**
-1. Review examples in `04_scaling_performance/`
-2. Study `06_real_world/` for complete architectures
-3. Check deployment docs in each example's README
-
-## Flash CLI Commands
-
-The Flash CLI provides a complete toolkit for building, testing, and deploying distributed inference applications.
-
-### Core Commands
+## CLI Commands
 
 ```bash
-flash init [project]         # Create new Flash project
-flash run                    # Run development server (localhost:8888)
-flash build                  # Build deployment package
-flash deploy --env <name>    # Build and deploy to environment
-flash undeploy <name>        # Delete deployed endpoint
+flash login              # Authenticate with Runpod (opens browser)
+flash run                # Run development server (localhost:8888)
+flash build              # Build deployment package
+flash deploy --env <name># Build and deploy to environment
+flash undeploy <name>    # Delete deployed endpoint
 ```
 
-### Environment Management
-
-```bash
-flash env list               # Show all environments
-flash env create <name>      # Create new environment (dev, staging, prod)
-flash env get <name>         # Show environment details
-flash env delete <name>      # Delete environment
-```
-
-### Application Management
-
-```bash
-flash app list               # List all Flash apps
-flash app create <name>      # Create new app
-flash app get <name>         # Show app details
-flash app delete --app <name># Delete app and all resources
-```
-
-### Command Options
-
-Many commands support additional options for customization:
-
-```bash
-flash run --host 0.0.0.0 --port 9000     # Custom host and port
-flash build --exclude torch,torchvision   # Exclude packages (reduce size)
-flash deploy --env prod --preview         # Local preview before deploying
-flash undeploy --all --force              # Remove all endpoints
-```
-
-### Full Documentation
-
-**[Complete CLI Reference](CLI-REFERENCE.md)** - Comprehensive guide with all commands, options, and examples
-
-**Step-by-Step Guides:**
-- [Getting Started (5 minutes)](docs/cli/getting-started.md) - Your first Flash project
-- [Command Reference](docs/cli/commands.md) - Exhaustive documentation for all commands
-- [Workflows](docs/cli/workflows.md) - Common development workflows
-- [Troubleshooting](docs/cli/troubleshooting.md) - Solutions to common problems
-
-### Quick Start
-
-```bash
-# 1. Create project
-flash init my-api && cd my-api
-
-# 2. Run locally
-flash run
-# Visit http://localhost:8888/docs
-
-# 3. Create environment and deploy
-flash env create production
-flash deploy --env production
-```
-
-## Testing Your Application
-
-After running `flash run`, you can test your API in two ways:
-
-**Option A: Using the Interactive UI**
-
-Visit **http://localhost:8888/docs** to use FastAPI's built-in Swagger UI where you can:
-- See all available endpoints
-- Test requests directly in your browser
-- View request/response schemas
-
-**Option B: Using curl**
-
-Test endpoints from the command line:
-```bash
-curl -X POST http://localhost:8888/endpoint \
-  -H "Content-Type: application/json" \
-  -d '{"key": "value"}'
-```
-
-See individual example READMEs for specific endpoint examples.
-
-## Unified App Architecture
-
-The root [main.py](main.py) provides a programmatic discovery system that automatically finds and loads all examples:
-
-**Discovery Process**:
-1. Scans all example category directories (`01_getting_started/`, `02_ml_inference/`, etc.)
-2. Detects two patterns:
-   - **Queue-based workers**: `@Endpoint(...)` decorated functions
-   - **Load-balanced workers**: `Endpoint` instances with `.get()/.post()` route decorators
-3. Dynamically imports and registers all endpoints with unique prefixes (e.g., `/01_hello_world/gpu/`)
-4. Generates metadata and documentation automatically
-
-**Benefits**:
-- Add new examples without modifying the unified app
-- Consistent routing across all examples
-- Single entry point for exploring all functionality
-- Automatic discovery eliminates manual registration
-
-## Example Structure
-
-Each example follows this structure:
-
-```
-example_name/
-├── README.md              # Documentation and deployment guide
-├── gpu_worker.py          # GPU worker with @Endpoint decorator
-├── cpu_worker.py          # CPU worker with @Endpoint decorator
-├── requirements.txt       # Python dependencies
-├── pyproject.toml         # Project configuration
-└── .env.example           # Environment variable template
-```
-
-### Dependency Management
-
-The unified app automatically discovers and loads all examples at runtime, which requires all example dependencies to be installed in the root environment.
-
-**Automatic Dependency Syncing**:
-
-When adding a new example with additional dependencies:
-
-1. Define dependencies in your example's `pyproject.toml`
-2. Run `make sync-example-deps` to update the root dependencies
-3. Run `uv sync --all-groups` to install the new packages
-4. Run `make requirements.txt` to regenerate the lockfile
-
-The sync script automatically:
-- Scans all example directories for `pyproject.toml` files
-- Merges dependencies into the root configuration
-- Filters out transitive dependencies already provided by `runpod-flash`
-- Detects version conflicts and uses the most permissive constraint
-- Preserves essential root dependencies (numpy, torch, runpod-flash)
-
-**Example**:
-
-```bash
-# After adding a new example with pillow and structlog dependencies
-make sync-example-deps  # Syncs example deps to root pyproject.toml
-uv sync --all-groups    # Installs new dependencies
-make requirements.txt   # Regenerates lockfile
-```
-
-This automation ensures that `flash run` from the root directory always has access to all required dependencies for dynamic example loading.
+See **[CLI-REFERENCE.md](./CLI-REFERENCE.md)** for complete documentation.
 
 ## Key Concepts
 
@@ -350,9 +82,9 @@ The `Endpoint` class configures functions for execution on Runpod's serverless i
 **Queue-based (one function = one endpoint):**
 
 ```python
-from runpod_flash import Endpoint, GpuGroup
+from runpod_flash import Endpoint, GpuType
 
-@Endpoint(name="my-worker", gpu=GpuGroup.ADA_24, workers=(0, 3), dependencies=["torch"])
+@Endpoint(name="my-worker", gpu=GpuType.NVIDIA_GEFORCE_RTX_4090, workers=(0, 3), dependencies=["torch"])
 async def process(data: dict) -> dict:
     import torch
     # this code runs on Runpod GPUs
@@ -389,14 +121,18 @@ print(job.output)
 ### Resource Types
 
 **GPU Workers** (`gpu=`):
-- `GpuGroup.ADA_24` - RTX 4090 (24GB)
-- `GpuGroup.ADA_48_PRO` - RTX 6000 Ada, L40 (48GB)
-- `GpuGroup.AMPERE_80` - A100 (80GB)
+| Type | Use Case |
+|------|----------|
+| `GpuType.NVIDIA_GEFORCE_RTX_4090` | RTX 4090 (24GB) |
+| `GpuType.NVIDIA_RTX_6000_ADA_GENERATION` | RTX 6000 Ada (48GB) |
+| `GpuType.NVIDIA_A100_80GB_PCIe` | A100 (80GB) |
 
 **CPU Workers** (`cpu=`):
-- `CpuInstanceType.CPU3G_2_8` - 2 vCPU, 8GB RAM
-- `CpuInstanceType.CPU3C_4_8` - 4 vCPU, 8GB RAM (Compute)
-- `CpuInstanceType.CPU5G_4_16` - 4 vCPU, 16GB RAM (Latest)
+| Type | Specs |
+|------|-------|
+| `cpu3g-2-8` | 2 vCPU, 8GB RAM |
+| `cpu3c-4-8` | 4 vCPU, 8GB RAM (Compute) |
+| `cpu5c-4-16` | 4 vCPU, 16GB RAM (Latest) |
 
 ### Auto-Scaling
 
@@ -405,30 +141,16 @@ Workers automatically scale based on demand:
 - `workers=(1, 5)` - Keep 1 warm, scale up to 5
 - `idle_timeout=5` - Minutes before scaling down
 
-## Contributing
-
-We welcome contributions! See [CONTRIBUTING.md](./CONTRIBUTING.md) for contribution guidelines and [DEVELOPMENT.md](./DEVELOPMENT.md) for development setup.
-
-To add a new example:
-1. Follow the standard example structure
-2. Include comprehensive README with deployment steps
-3. Add tests for critical functionality
-4. Ensure all dependencies are pinned in requirements.txt
-5. Run `make quality-check` before committing
-6. Test deployment with `flash deploy`
-
 ## Resources
 
-- [Flash CLI Documentation](https://github.com/runpod/runpod-flash)
+- [Flash Documentation](https://docs.runpod.io)
 - [Runpod Serverless Docs](https://docs.runpod.io/serverless/overview)
-- [Flash SDK Reference](https://github.com/runpod/runpod-flash)
 - [Community Discord](https://discord.gg/runpod)
 
-## Testing
+## Contributing
 
-All examples are continuously tested against Python 3.10-3.14 to ensure compatibility across all supported versions. See [.github/workflows/](./.github/workflows/) for CI configuration.
+See [CONTRIBUTING.md](./CONTRIBUTING.md) for contribution guidelines and [DEVELOPMENT.md](./DEVELOPMENT.md) for development setup.
 
 ## License
 
 MIT License - see [LICENSE](./LICENSE) for details.
-
diff --git a/docs/cli/commands.md b/docs/cli/commands.md
index ae02f64..9c309f0 100644
--- a/docs/cli/commands.md
+++ b/docs/cli/commands.md
@@ -4,6 +4,7 @@ Exhaustive documentation for all Flash CLI commands. This guide covers every opt
 
 ## Table of Contents
 
+- [flash login](#flash-login) - Authenticate with Runpod
 - [flash init](#flash-init) - Create new Flash project
 - [flash run](#flash-run) - Run development server
 - [flash build](#flash-build) - Build deployment package
@@ -22,6 +23,46 @@ Exhaustive documentation for all Flash CLI commands. This guide covers every opt
 
 ---
 
+## flash login
+
+Authenticate with Runpod by opening a browser for OAuth authentication.
+
+### Synopsis
+
+```bash
+flash login
+```
+
+### Description
+
+Authenticates with Runpod by opening your default browser to the Runpod authentication page. After successful authentication, credentials are saved locally and persist across terminal sessions.
+
+This is the recommended authentication method for interactive use. For CI/CD or automated environments, use the `RUNPOD_API_KEY` environment variable instead.
+
+### Examples
+
+**Authenticate with Runpod:**
+```bash
+flash login
+```
+
+**Alternative: Manual API key configuration:**
+```bash
+# Set environment variable
+export RUNPOD_API_KEY=your-key-here
+
+# Or add to .env file
+echo "RUNPOD_API_KEY=your-key-here" > .env
+```
+
+### Notes
+
+- Requires a browser for OAuth flow
+- Credentials are stored securely on your local machine
+- For headless environments, use `RUNPOD_API_KEY` environment variable
+
+---
+
 ## flash init
 
 Create a new Flash project with the correct structure, boilerplate code, and configuration files.
@@ -179,12 +220,12 @@ The generated `.gitignore` already includes necessary patterns.
 
 2. **Install Dependencies**
    ```bash
-   pip install -e .
+   uv sync && uv pip install -e .
    ```
 
 3. **Run Locally**
    ```bash
-   flash run
+   uv run flash run
    ```
 
 4. **View Documentation**
diff --git a/docs/cli/getting-started.md b/docs/cli/getting-started.md
index 940b8f0..04f3a79 100644
--- a/docs/cli/getting-started.md
+++ b/docs/cli/getting-started.md
@@ -7,30 +7,34 @@ Complete your first Flash project in under 10 minutes. This guide walks you thro
 Before starting, ensure you have:
 
 - **Python 3.10 or higher** - Check with `python --version`
+- **uv** - Install with `curl -LsSf https://astral.sh/uv/install.sh | sh`
 - **Runpod API Key** - Get from https://runpod.io/console/user/settings
-- **Flash installed** - Install with `pip install runpod-flash`
 
 ### Verify Installation
 
 ```bash
-flash --version
+uv run flash --version
 # Should output: flash, version X.Y.Z
 ```
 
-### Configure API Key
+### Authenticate
 
-Set your Runpod API key as an environment variable:
+The easiest way to authenticate is with `flash login`:
 
 ```bash
-export RUNPOD_API_KEY=your-key-here
+uv run flash login
 ```
 
-Or add to `.env` file:
+This opens a browser for authentication and saves your credentials.
+
+**Alternative:** Set your Runpod API key manually:
 ```bash
+export RUNPOD_API_KEY=your-key-here
+# Or add to .env file:
 echo "RUNPOD_API_KEY=your-key-here" > .env
 ```
 
-**Checkpoint:** Running `echo $RUNPOD_API_KEY` should display your key.
+**Checkpoint:** Running `uv run flash login` or `echo $RUNPOD_API_KEY` confirms authentication.
 
 ---
 
@@ -41,7 +45,7 @@ echo "RUNPOD_API_KEY=your-key-here" > .env
 Create a new Flash project with the CLI:
 
 ```bash
-flash init hello-flash
+uv run flash init hello-flash
 cd hello-flash
 ```
 
@@ -88,7 +92,7 @@ async def process_request(payload: dict) -> dict:
 Start the development server:
 
 ```bash
-flash run
+uv run flash run
 ```
 
 **Expected output:**
@@ -152,7 +156,7 @@ curl -X POST http://localhost:8888/process \
 Stop the development server (Ctrl+C), then create a deployment environment:
 
 ```bash
-flash env create dev
+uv run flash env create dev
 ```
 
 **Expected output:**
@@ -164,7 +168,7 @@ Environment 'dev' created successfully
 - Created a deployment target named "dev"
 - This environment will contain your deployed endpoints
 
-**Checkpoint:** Run `flash env list` and verify "dev" appears.
+**Checkpoint:** Run `uv run flash env list` and verify "dev" appears.
 
 ---
 
@@ -173,7 +177,7 @@ Environment 'dev' created successfully
 Package your application for deployment:
 
 ```bash
-flash build
+uv run flash build
 ```
 
 **Expected output:**
@@ -200,7 +204,7 @@ Creating archive...
 Deploy your application to the "dev" environment:
 
 ```bash
-flash deploy --env dev
+uv run flash deploy --env dev
 ```
 
 **Expected output:**
@@ -289,7 +293,8 @@ The flash-examples repository contains production-ready examples:
 ```bash
 git clone https://github.com/runpod/flash-examples.git
 cd flash-examples
-flash run
+uv sync && uv pip install -e .
+uv run flash run
 # Visit http://localhost:8888/docs to explore all examples
 ```
 
@@ -331,9 +336,11 @@ flash run
 
 **Solution:**
 ```bash
-pip install runpod-flash
+# Install uv if needed
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
 # Verify installation
-flash --version
+uv run flash --version
 ```
 
 ### Port Already in Use
@@ -343,7 +350,7 @@ flash --version
 **Solution:**
 ```bash
 # Use different port
-flash run --port 9000
+uv run flash run --port 9000
 
 # Or find and kill process using port 8888
 lsof -ti:8888 | xargs kill -9
@@ -367,7 +374,7 @@ echo $RUNPOD_API_KEY
 **Solution:**
 ```bash
 # Exclude packages present in Runpod base image
-flash build --exclude torch,torchvision,torchaudio
+uv run flash build --exclude torch,torchvision,torchaudio
 ```
 
 See [Troubleshooting Guide](troubleshooting.md) for more solutions.
@@ -378,13 +385,13 @@ See [Troubleshooting Guide](troubleshooting.md) for more solutions.
 
 | Command | Purpose |
 |---------|---------|
-| `flash init <name>` | Create new project |
-| `flash run` | Run development server |
-| `flash build` | Build deployment package |
-| `flash deploy --env <name>` | Deploy to environment |
-| `flash env create <name>` | Create environment |
-| `flash env list` | List environments |
-| `flash undeploy <name>` | Delete endpoint |
+| `uv run flash init <name>` | Create new project |
+| `uv run flash run` | Run development server |
+| `uv run flash build` | Build deployment package |
+| `uv run flash deploy --env <name>` | Deploy to environment |
+| `uv run flash env create <name>` | Create environment |
+| `uv run flash env list` | List environments |
+| `uv run flash undeploy <name>` | Delete endpoint |
 
 ---
 
diff --git a/docs/cli/troubleshooting.md b/docs/cli/troubleshooting.md
index 44ac31a..9f0cc58 100644
--- a/docs/cli/troubleshooting.md
+++ b/docs/cli/troubleshooting.md
@@ -29,7 +29,16 @@ bash: flash: command not found
 
 **Solutions:**
 
-**1. Install Flash:**
+**1. Install with uv (recommended):**
+```bash
+# Install uv if needed
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
+# Verify installation
+uv run flash --version
+```
+
+**2. Install with pip (alternative):**
 ```bash
 pip install runpod-flash
 
@@ -37,7 +46,7 @@ pip install runpod-flash
 flash --version
 ```
 
-**2. Check PATH:**
+**3. Check PATH:**
 ```bash
 # Find where flash is installed
 which flash
diff --git a/docs/cli/workflows.md b/docs/cli/workflows.md
index 7ecc93e..3283969 100644
--- a/docs/cli/workflows.md
+++ b/docs/cli/workflows.md
@@ -46,19 +46,21 @@ cd my-api
 #### 2. Set Up Environment
 
 ```bash
-# Create virtual environment (if needed)
+# Install dependencies with uv (recommended)
+uv sync && uv pip install -e .
+```
+
+**Alternative with pip:**
+```bash
 python -m venv .venv
 source .venv/bin/activate  # macOS/Linux
-# .venv\Scripts\activate  # Windows
-
-# Install dependencies
 pip install -e .
 ```
 
 **Validation:**
 ```bash
 python --version  # Should show 3.10+
-pip list | grep runpod-flash  # Should show runpod-flash
+uv run flash --version  # Should show flash version
 ```
 
 #### 3. Configure Environment Variables