Understand AI-Assisted Software Development: Become a 10x Developer

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Learn to think like a Software Developer while using AI to exponentially increase your effectiveness and efficiency as a developer. Build real knowledge and use strategic workflows to plan, generate, review and improve production-ready code.

What you’ll learn

The mental model to level-up your Software Developement skills in the AI Age
Plan software features with AI assistance and guide AI through structured implementation workflows
Build and author reusable Agent Skills with engineered context for more efficient work
Review and correct AI-generated code while avoiding dependency, security, and quality pitfalls
Table of Contents
1 Understand AI-Assisted Software Development Become a 10x Developer
2 Setup You and Your LLM
3 Introduction
4 LLMs and Grammar
5 Conceptual Aside Vectors
6 Attention and Attending
7 Conceptual Aside Determinism vs. Non-Determinism
8 Determinism and the Digital Age
9 Conceptual Aside Programming Language Grammar
10 Prediction and Statistics
11 Confabulation and Unreliability
12 Conceptual Aside Reasoning Models
13 Conceptual Aside Agents
14 Conversation and the Dangers of Anthropomorphization
15 Introduction
16 Pattern Matching and Navigating the Embedding Space
17 Is Context _Engineering_ Engineering_
18 Project Context
19 Technical Context
20 Context Refresh and Drift
21 Immediate Context
22 Task Context
23 Clean Human Code
24 Agents and Context
25 Introduction
26 The Anatomy of an Effective Prompt
27 Task Decomposition
28 Roles and Personas
29 Specificity and Constraints
30 Examples of Expected Behavior
31 Session Context
32 Introduction
33 Brainstorming
34 Business Rules and Constraints
35 Documentation
36 Implementation Planning
37 The Context Problem
38 Conceptual Aside Context Window
39 The Lighthouse Model of LLMs
40 Context Window Size
41 Conceptual Aside System Prompt
42 Context Rot
43 Skills
44 Conceptual Aside Markdown
45 The Anatomy of a Skill
46 Frontmatter
47 Instructions
48 Scripts
49 Assets
50 How Agents Integrate Skills
51 Conceptual Aside Progressive Disclosure
52 Discover the Skills on the Filesystem
53 Load the Metadata
54 Match Tasks to Skills
55 Activate the Skill
56 Execute and Access
57 Skills in Action
58 Skill Authoring
59 Authoring the Metadata
60 Good Context
61 Domain Expertise
62 New Capabilities
63 Repeatable Workflows
64 Interoperability
65 Finding Skills
66 Skill Project
67 Introduction
68 Task Decomposition
69 Rules
70 Code Constraints (Types, Tests, and Patterns)
71 The Model Context Protocol
72 Agent Skills
73 Agent Orchestration
74 Introduction
75 Human-In-The-Loop
76 AI-Assisted Debugging
77 Iterative Refinement and Not Breaking What’s Working
78 Team Collaboration When AI is a Team Member
79 Established Patterns
80 Introduction
81 Explainability
82 Systems Integration
83 Edge Cases
84 Performance
85 Introduction
86 Hallucinations
87 The Limitations of AI Training Data
88 The Echo Chamber Effect
89 Cognitive Load
90 A Stranger to Your Codebase
91 Maintainability
92 Context Switching
93 Cognitive Laziness and Maintaining Your Skill
94 Losing the Joy of Coding
95 Don’t Imitate, Understand!
96 Exercise Imposter Syndrome
97 Integrated Development Environments (IDEs) and Completions
98 Introduction
99 Conversations
100 Agents and Iteration
101 Hype
102 Introduction
103 Planning
104 Implementation
105 Integration
106 Quality Control
107 Conclusion
108 Thank You!