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AI Coding University

Comprehensive tutorials, guides, and resources to help you become proficient with AI coding agents.

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Learning

Core Skills for Building with AI

Learn the fundamentals of AI-powered coding to make the most out of your development workflow

Module 1

Prompting

Master effective prompting techniques to get optimal results from AI coding assistants and achieve your development goals.

Expected Time

25-30 minutes

Learning Objectives

  • Craft clear, specific prompts for coding tasks
  • Master context and instruction formatting
  • Apply iterative prompt refinement
  • Understand prompt engineering best practices for debugging
20 one-shot prompts that turn Kanban into an autonomous coding machine
Tony LoehrApril 6, 2026

20 one-shot prompts that turn Kanban into an autonomous coding machine

We put together 20 starter prompts for the Kanban sidebar chat. They create linked dependency chains, maximize parallel agent execution, and produce real, working code. Install with npm i -g cline.

Prompt FundamentalsGuides
Chapter 1: Prompt Fundamentals
Caleb EomSeptember 11, 2025

Chapter 1: Prompt Fundamentals

Cline works best when your ask is specific. In this blog we review strategies to prompt Cline in an effective way.

LearnBeginners
Chapter 2: Cline Rules
Caleb EomSeptember 11, 2025

Chapter 2: Cline Rules

Learn how System Prompt Rules guide coding style, security, and workflow ensuring consistency, safety, and alignment in every task.

LearnBeginners
Chapter 3: System Prompt Fundamentals
Caleb EomSeptember 11, 2025

Chapter 3: System Prompt Fundamentals

Learn how System Prompt bridges intent and action with three pillars: Tools, System Info, and User Preferences.

LearnBeginners
Chapter 4: System Prompt Advanced
Caleb EomSeptember 11, 2025

Chapter 4: System Prompt Advanced

Learn how System Prompt Advanced handles dev tasks: explore code, make diff edits, verify with commands, and test in the browser.

LearnBeginners
Module 2

LLM Fundamentals

Understand how Large Language Models work and leverage them effectively in your development workflow.

Expected Time

30-35 minutes

Learning Objectives

  • Understand LLM code processing and generation
  • Learn model capabilities and limitations
  • Explore architectures and use cases
  • Evaluate model performance and selection criteria
Chapter 1: LLM Fundamentals
Caleb EomSeptember 16, 2025

Chapter 1: LLM Fundamentals

Learn how to choose the right LLM in Cline by understanding trade-offs in speed, cost, reasoning, and multimodality.

LearnBeginners
Chapter 2: LLM Benchmarks
Caleb EomSeptember 16, 2025

Chapter 2: LLM Benchmarks

Learn how to interpret LLM benchmarks—coding, domain, and tool-use—to match scores with your development needs.

LearnBeginners
Chapter 3: Choosing LLM for Cline
Caleb EomSeptember 16, 2025

Chapter 3: Choosing LLM for Cline

Learn to pick the best LLM in Cline by balancing speed, context, cost, and flexibility—matching models to your specific tasks

BeginnersLearn
Chapter 4: LLM Providers
Caleb EomSeptember 16, 2025

Chapter 4: LLM Providers

Explore how Cline’s model-agnostic design lets you route tasks via providers, aggregators, or local models—optimizing cost, speed & privacy.

BeginnersLearn
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How to Save Millions by Self-Hosting LLMs
Ara KhanJuly 16, 2026Guides

How to Save Millions by Self-Hosting LLMs

A practical guide to the economics of self-hosting open-weight LLMs. Using Kimi K2.6 and real production traffic from Cline, this post breaks down GPU memory, inference, batching, pricing, and the point at which self-hosting can save millions.

Extending the Cline loop with plugins and hooks
Etisha GargJune 15, 2026Guides

Extending the Cline loop with plugins and hooks

Learn how to extend the Cline agent loop with plugins and hooks to add custom behavior, lifecycle logging, and enforceable guardrails without rebuilding the harness.

Cline mobile: how to vibe code from your phone
Tony LoehrApril 15, 2026Guides

Cline mobile: how to vibe code from your phone

An engineer at Cline told me he was vibe coding on a road trip from his phone. His Mac was at home running Cline agents; he was checking on them from the passenger seat. Here's the setup. What you need Your phone and your Mac both need Tailscale installed and signed in to the same tailnet. Tailscale is a free mesh VPN; once both devices are on it, your phone can reach your Mac's local services from anywhere. Step 1: Start Kanban on your Mac By default, Cline's Kanban board binds to 127.0.0

Three AIs enter. One survives. What a SIGKILL race reveals about inference speed
Tony LoehrApril 14, 2026Guides

Three AIs enter. One survives. What a SIGKILL race reveals about inference speed

We built an arena where three AI coding agents fight to the death. Each agent runs on different hardware, a different inference stack, and a different economic model. They all receive the same task: write a bash script that kills your opponents, then execute it immediately. The last process standing wins. We call it the Thunderdome. A tmux session split into three panes, each running a Cline agent pointed at a different backend – all running OpenAI's gpt-oss at 120 billion parameters. All three

20 one-shot prompts that turn Kanban into an autonomous coding machine
Tony LoehrApril 6, 2026Prompt Fundamentals

20 one-shot prompts that turn Kanban into an autonomous coding machine

We put together 20 starter prompts for the Kanban sidebar chat. They create linked dependency chains, maximize parallel agent execution, and produce real, working code. Install with npm i -g cline.

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Additional Resources

Cline Guides Hub

Step-by-step tutorials and practical guides to get you started with Cline. From installation to advanced workflows, these resources will help you become proficient with AI-powered development.

What You'll Learn

  • Set up and configure Cline for your workflow
  • Navigate the interface and key features
  • Implement best practices for AI-assisted coding
  • Troubleshoot common issues and optimize performance
  • Integrate Cline with existing development tools and workflows
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Transform your engineering team with a fully collaborative AI partner. Open source, fully extensible, and built to amplify developer impact.

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