Example Curriculum
Section 0: Introduction
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days
days
after you enroll
Section 1: A Proper Mental Model of LLMs
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days
days
after you enroll
- Introduction (1:32)
- LLMs and Grammar (11:25)
- Conceptual Aside: Vectors (4:20)
- Attention and Attending (4:43)
- Conceptual Aside: Determinism vs. Non-Determinism (3:12)
- Determinism and the Digital Age (2:13)
- Conceptual Aside: Programming Language Grammar (1:53)
- Prediction and Statistics (7:06)
- Confabulation and Unreliability (4:14)
- Conceptual Aside: Reasoning Models (2:33)
- Conceptual Aside: Agents (1:58)
- Conversation and the Dangers of Anthropomorphization (3:24)
- Let's Have Some Fun (+ More Resources)
Section 2: Context "Engineering" and Management
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days
days
after you enroll
- Introduction (0:24)
- Pattern Matching and Navigating the Embedding Space (2:01)
- Is Context "Engineering" Engineering? (2:40)
- Project Context (4:03)
- Technical Context (2:04)
- Context Refresh and Drift (4:27)
- Immediate Context (2:45)
- Task Context (2:30)
- Clean Human Code (2:39)
- Agents and Context (2:12)
- Unlimited Updates
Section 3: Prompt "Engineering"
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days
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Section 4: Planning Process
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Section 5: Agent Skills
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days
days
after you enroll
- The Context Problem (0:24)
- Conceptual Aside: Context Window (1:49)
- The Lighthouse Model of LLMs (9:00)
- Context Window Size (1:43)
- Conceptual Aside: System Prompt (4:42)
- Context Rot (1:58)
- Skills (0:19)
- Conceptual Aside: Markdown (1:53)
- The Anatomy of a Skill (2:29)
- Frontmatter (4:06)
- Instructions (3:06)
- Scripts (3:35)
- Assets (2:05)
- How Agents Integrate Skills (0:36)
- Conceptual Aside: Progressive Disclosure (1:11)
- Discover the Skills on the Filesystem (2:20)
- Load the Metadata (3:12)
- Match Tasks to Skills (4:11)
- Activate the Skill (2:12)
- Execute and Access (5:25)
- Skills in Action (4:11)
- Skill Authoring (0:20)
- Authoring the Metadata (2:32)
- Good Context (1:46)
- Domain Expertise (1:47)
- New Capabilities (1:52)
- Good Context: An Open Source Education
- Repeatable Workflows (11:33)
- Interoperability (1:46)
- Finding Skills (1:13)
- Skill Project (1:38)
- Create a Skill
Section 6: Implementation
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days
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Section 7: Integration
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Section 8: Verification and Quality Control
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days
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Section 9: The Pitfalls of AI, LLMs
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days
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- Introduction (1:00)
- Hallucinations (5:05)
- The Limitations of AI Training Data (3:39)
- The Echo Chamber Effect (3:57)
- Cognitive Load (4:20)
- A Stranger to Your Codebase (4:18)
- Maintainability (3:09)
- Context Switching (2:18)
- Cognitive Laziness and Maintaining Your Skill (3:30)
- Losing the Joy of Coding (2:52)
- Don't Imitate, Understand! (2:59)
- Exercise: Imposter Syndrome (2:55)
Section 10: Practical Tooling in AI
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days
days
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Section 11: Capstone Project
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Section 12: Where To Go From Here?
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