promptgarten 🌱

Your path to agent whisperer

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πŸ—ΊοΈ YOUR LEARNING MAP β€” COMPLETED CHAPTERS LIGHT UP

WORLD 0 Β· GETTING STARTED0/5 done Β· 0%Installing Claude Code (Step by Step)πŸ› οΈWhich Model, Which Plan?πŸ› οΈGit & GitHub for Vibe CodersπŸ› οΈClaude Code: Anthropic's CLI AgentπŸ› οΈCLAUDE.md / AGENTS.md: Give Your Agent Memory & RulesπŸ› οΈWORLD 1 Β· BASICS0/20 done Β· 0%Terminal Basics for BeginnersπŸ› οΈWhat Is an LLM?πŸ“–Tokens (and Why They Cost Money)πŸ“–Context WindowπŸ“–What Is a Prompt?πŸ“–Pattern: Feed Context Instead of Asking Vaguely✍️System Prompt vs. User PromptπŸ“–Temperature and Sampling: Why the Same Prompt Gives Different AnswersπŸ“–Hallucination: Why AI Confidently LiesπŸ“–Prompt Structures: Layout That Improves Results✍️Few-Shot Examples: Show, Don't Just Tell✍️Role Prompts: What "You Are an Expert..." Actually Changes✍️Pattern: Plan First, Then Code✍️AI Coding IDE vs. CLI: Two Ways to Work With an AgentπŸ’‘Reasoning Models: When a Model Thinks Before It AnswersπŸ“–Streaming: Why Answers Appear Word by WordπŸ“–Speculative Decoding: A Small Model Guesses, the Big One ChecksπŸ“–Knowledge Distillation: Training a Small Model to Copy a Big OneπŸ“–Rate Limits and Quotas: Why AI Tools Sometimes Say Slow DownπŸ“–AI-Generated Code and Licensing: Who Actually Owns It?πŸ’‘WORLD 2 Β· AGENTS0/20 done Β· 0%What Is an AI Agent? (vs. a Chatbot)πŸ’‘The Agent Loop: Think β†’ Act β†’ Check β†’ RepeatπŸ’‘Tool Use: How LLMs Call ToolsπŸ’‘Forcing Output Formats: From Prompt Tricks to Guaranteed Schemas✍️Vibe Coding: When It Works, When It Bites YouπŸ’‘What Are Subagents?πŸ’‘Guardrails for Autonomous AgentsπŸ’‘Sandboxing: Why Agents Should Run IsolatedπŸ’‘Securing Agents in PracticeπŸ› οΈHuman-in-the-Loop: Where People Should Still Check the WorkπŸ’‘Data Privacy and AI Tools: What Actually Leaves Your MachineπŸ› οΈLoops for Agents: Letting AI Iterate AutonomouslyπŸ’‘Multi-agent patternsπŸ’‘Agent Teams: Multiple Agents, One ProjectπŸ’‘Debugging with AI Agents: Systematic, Not GuessworkπŸ› οΈSelf-Critique Loops: Have the Model Check Its Own Work✍️Web Search and Grounding: Letting Agents Fetch Current FactsπŸ’‘Context strategies for agentsπŸ’‘How AI Agents Remember ThingsπŸ’‘Red-Teaming Your Own Agent SetupπŸ› οΈWORLD 3 Β· TOOLBOX0/32 done Β· 0%Slash Commands, Hooks & More: Steering Claude CodeπŸ› οΈPermission Modes for AgentsπŸ› οΈSkills: Knowledge Your Agent Can LoadπŸ“–Writing Your Own Commands: Save Recurring PromptsπŸ› οΈPlugins: Extensions for AI Coding ToolsπŸ“–MCP (Model Context Protocol): How AI Tools ConnectπŸ“–Hooks in Claude CodeπŸ› οΈGit worktrees for parallel AI agentsπŸ› οΈCheckpoints and Rollbacks: Your Undo Button for Agent WorkπŸ› οΈHeadless Mode: Running Agents Without InteractionπŸ› οΈFrom GitHub Issue to Pull Request: Letting an Agent Do the WorkπŸ› οΈCost Control for AI AgentsπŸ› οΈModel Routing: The Right Model for the Right TaskπŸ’‘Caching Strategies: Prompt Caching & Context CachingπŸ’‘Testing with Agents: Generate Tests and Use Them as a GateπŸ› οΈEvals – systematically testing prompts and modelsπŸ’‘Safe Refactoring with AI AgentsπŸ› οΈUnderstanding Unfamiliar Code with AIπŸ› οΈBuilding a Simple RAG System YourselfπŸ› οΈVector Databases: Where Embeddings Actually LiveπŸ“–Chunking Strategies: How to Split Text for RAGπŸ’‘Retrieval Evaluation: Is Your RAG System Finding the Right Thing?πŸ’‘Fine-Tuning or Prompting? A Decision GuideπŸ› οΈMCP Security: The Risks of Connecting Tools to an AgentπŸ’‘Getting Your Project Online (Deployment)πŸ› οΈReading Benchmarks Without Getting FooledπŸ› οΈSWE-bench, Terminal-Bench & Co.: Reading Coding-Agent BenchmarksπŸ’‘Quantization: Squeezing Model Weights Down to FitπŸ“–Mixture of Experts: Huge Models That Only Use a Slice of ThemselvesπŸ“–Optimizing Latency: Making Agents Feel FastπŸ› οΈPrompt Versioning: Treating Prompts Like CodeπŸ› οΈAgents Across Multiple RepositoriesπŸ› οΈ

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WORLD 0 Β· GETTING STARTED

β–Ά

1. Installing Claude Code (Step by Step)

+20 XP Β· 5 min Β· ●○○

Continue β†’
πŸ”’

2. Which Model, Which Plan?

+20 XP Β· 4 min Β· ●○○

πŸ”’

3. Git & GitHub for Vibe Coders

+20 XP Β· 5 min Β· ●○○

πŸ”’

4. Claude Code: Anthropic's CLI Agent

+40 XP Β· 4 min Β· ●●○

πŸ”’

5. CLAUDE.md / AGENTS.md: Give Your Agent Memory & Rules

+40 XP Β· 3 min Β· ●●○

WORLD 1 Β· BASICS

β–Ά

1. Terminal Basics for Beginners

+20 XP Β· 4 min Β· ●○○

Continue β†’
πŸ”’

2. What Is an LLM?

+20 XP Β· 3 min Β· ●○○

πŸ”’

3. Tokens (and Why They Cost Money)

+20 XP Β· 3 min Β· ●○○

πŸ”’

4. Context Window

+20 XP Β· 3 min Β· ●○○

πŸ”’

5. What Is a Prompt?

+20 XP Β· 2 min Β· ●○○

πŸ”’

6. Pattern: Feed Context Instead of Asking Vaguely

+20 XP Β· 3 min Β· ●○○

πŸ”’

7. System Prompt vs. User Prompt

+40 XP Β· 3 min Β· ●●○

πŸ”’

8. Temperature and Sampling: Why the Same Prompt Gives Different Answers

+40 XP Β· 4 min Β· ●●○

πŸ”’

9. Hallucination: Why AI Confidently Lies

+20 XP Β· 3 min Β· ●○○

πŸ”’

10. Prompt Structures: Layout That Improves Results

+20 XP Β· 4 min Β· ●○○

πŸ”’

11. Few-Shot Examples: Show, Don't Just Tell

+20 XP Β· 3 min Β· ●○○

πŸ”’

12. Role Prompts: What "You Are an Expert..." Actually Changes

+20 XP Β· 3 min Β· ●○○

πŸ”’

13. Pattern: Plan First, Then Code

+40 XP Β· 3 min Β· ●●○

πŸ”’

14. AI Coding IDE vs. CLI: Two Ways to Work With an Agent

+20 XP Β· 4 min Β· ●○○

πŸ”’

15. Reasoning Models: When a Model Thinks Before It Answers

+40 XP Β· 4 min Β· ●●○

πŸ”’

16. Streaming: Why Answers Appear Word by Word

+20 XP Β· 3 min Β· ●○○

πŸ”’

17. Speculative Decoding: A Small Model Guesses, the Big One Checks

+60 XP Β· 5 min Β· ●●●

πŸ”’

18. Knowledge Distillation: Training a Small Model to Copy a Big One

+60 XP Β· 5 min Β· ●●●

πŸ”’

19. Rate Limits and Quotas: Why AI Tools Sometimes Say Slow Down

+20 XP Β· 3 min Β· ●○○

πŸ”’

20. AI-Generated Code and Licensing: Who Actually Owns It?

+40 XP Β· 4 min Β· ●●○

WORLD 2 Β· AGENTS

β–Ά

1. What Is an AI Agent? (vs. a Chatbot)

+20 XP Β· 3 min Β· ●○○

Continue β†’
πŸ”’

2. The Agent Loop: Think β†’ Act β†’ Check β†’ Repeat

+40 XP Β· 4 min Β· ●●○

πŸ”’

3. Tool Use: How LLMs Call Tools

+40 XP Β· 4 min Β· ●●○

πŸ”’

4. Forcing Output Formats: From Prompt Tricks to Guaranteed Schemas

+40 XP Β· 4 min Β· ●●○

πŸ”’

5. Vibe Coding: When It Works, When It Bites You

+20 XP Β· 3 min Β· ●○○

πŸ”’

6. What Are Subagents?

+40 XP Β· 3 min Β· ●●○

πŸ”’

7. Guardrails for Autonomous Agents

+60 XP Β· 4 min Β· ●●●

πŸ”’

8. Sandboxing: Why Agents Should Run Isolated

+40 XP Β· 4 min Β· ●●○

πŸ”’

9. Securing Agents in Practice

+40 XP Β· 5 min Β· ●●○

πŸ”’

10. Human-in-the-Loop: Where People Should Still Check the Work

+40 XP Β· 4 min Β· ●●○

πŸ”’

11. Data Privacy and AI Tools: What Actually Leaves Your Machine

+40 XP Β· 5 min Β· ●●○

πŸ”’

12. Loops for Agents: Letting AI Iterate Autonomously

+60 XP Β· 5 min Β· ●●●

πŸ”’

13. Multi-agent patterns

+40 XP Β· 5 min Β· ●●●

πŸ”’

14. Agent Teams: Multiple Agents, One Project

+60 XP Β· 5 min Β· ●●●

πŸ”’

15. Debugging with AI Agents: Systematic, Not Guesswork

+40 XP Β· 5 min Β· ●●○

πŸ”’

16. Self-Critique Loops: Have the Model Check Its Own Work

+40 XP Β· 4 min Β· ●●○

πŸ”’

17. Web Search and Grounding: Letting Agents Fetch Current Facts

+40 XP Β· 4 min Β· ●●○

πŸ”’

18. Context strategies for agents

+40 XP Β· 5 min Β· ●●●

πŸ”’

19. How AI Agents Remember Things

+40 XP Β· 4 min Β· ●●○

πŸ”’

20. Red-Teaming Your Own Agent Setup

+60 XP Β· 5 min Β· ●●●

WORLD 3 Β· TOOLBOX

β–Ά

1. Slash Commands, Hooks & More: Steering Claude Code

+40 XP Β· 6 min Β· ●●○

Continue β†’
πŸ”’

2. Permission Modes for Agents

+40 XP Β· 5 min Β· ●●○

πŸ”’

3. Skills: Knowledge Your Agent Can Load

+40 XP Β· 4 min Β· ●●○

πŸ”’

4. Writing Your Own Commands: Save Recurring Prompts

+40 XP Β· 5 min Β· ●●○

πŸ”’

5. Plugins: Extensions for AI Coding Tools

+20 XP Β· 3 min Β· ●○○

πŸ”’

6. MCP (Model Context Protocol): How AI Tools Connect

+40 XP Β· 4 min Β· ●●○

πŸ”’

7. Hooks in Claude Code

+30 XP Β· 4 min Β· ●●○

πŸ”’

8. Git worktrees for parallel AI agents

+30 XP Β· 4 min Β· ●●○

πŸ”’

9. Checkpoints and Rollbacks: Your Undo Button for Agent Work

+40 XP Β· 4 min Β· ●●○

πŸ”’

10. Headless Mode: Running Agents Without Interaction

+40 XP Β· 5 min Β· ●●○

πŸ”’

11. From GitHub Issue to Pull Request: Letting an Agent Do the Work

+40 XP Β· 5 min Β· ●●○

πŸ”’

12. Cost Control for AI Agents

+40 XP Β· 4 min Β· ●●○

πŸ”’

13. Model Routing: The Right Model for the Right Task

+40 XP Β· 4 min Β· ●●○

πŸ”’

14. Caching Strategies: Prompt Caching & Context Caching

+40 XP Β· 5 min Β· ●●○

πŸ”’

15. Testing with Agents: Generate Tests and Use Them as a Gate

+40 XP Β· 5 min Β· ●●○

πŸ”’

16. Evals – systematically testing prompts and models

+30 XP Β· 4 min Β· ●●○

πŸ”’

17. Safe Refactoring with AI Agents

+40 XP Β· 4 min Β· ●●●

πŸ”’

18. Understanding Unfamiliar Code with AI

+40 XP Β· 4 min Β· ●●○

πŸ”’

19. Building a Simple RAG System Yourself

+60 XP Β· 6 min Β· ●●●

πŸ”’

20. Vector Databases: Where Embeddings Actually Live

+40 XP Β· 5 min Β· ●●○

πŸ”’

21. Chunking Strategies: How to Split Text for RAG

+40 XP Β· 5 min Β· ●●○

πŸ”’

22. Retrieval Evaluation: Is Your RAG System Finding the Right Thing?

+60 XP Β· 5 min Β· ●●●

πŸ”’

23. Fine-Tuning or Prompting? A Decision Guide

+40 XP Β· 4 min Β· ●●○

πŸ”’

24. MCP Security: The Risks of Connecting Tools to an Agent

+60 XP Β· 6 min Β· ●●●

πŸ”’

25. Getting Your Project Online (Deployment)

+40 XP Β· 6 min Β· ●●○

πŸ”’

26. Reading Benchmarks Without Getting Fooled

+40 XP Β· 5 min Β· ●●○

πŸ”’

27. SWE-bench, Terminal-Bench & Co.: Reading Coding-Agent Benchmarks

+60 XP Β· 5 min Β· ●●●

πŸ”’

28. Quantization: Squeezing Model Weights Down to Fit

+40 XP Β· 4 min Β· ●●○

πŸ”’

29. Mixture of Experts: Huge Models That Only Use a Slice of Themselves

+60 XP Β· 5 min Β· ●●●

πŸ”’

30. Optimizing Latency: Making Agents Feel Fast

+40 XP Β· 4 min Β· ●●○

πŸ”’

31. Prompt Versioning: Treating Prompts Like Code

+40 XP Β· 4 min Β· ●●○

πŸ”’

32. Agents Across Multiple Repositories

+60 XP Β· 5 min Β· ●●●

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