CF

AI Coding for Real Engineers

10h 5s
English
Paid

AI Coding for Real Engineers is a 92-lesson 10 hours self-paced course by Matt Pocock. A two-week intensive course for developers who want to implement AI tools in real production: from context management and architectural planning to autonomous agents and effective code review.

Course facts

Lessons
92
Duration
10 hours
Level
All levels
Language
English
Updated
Instructor
Matt Pocock
Price
Premium

A two-week intensive course for developers who want to implement AI tools in real production: from context management and architectural planning to autonomous agents and effective code review.

Are you using AI correctly?

I am. And daily development with the help of neural networks has completely changed my perspective on modern engineering work.

The main thing I realized is that AI is both hype and a powerful tool. But the potential is unlocked only for those who possess the skill of systematic design.

Inexperienced use of AI (for example, Claude Code) creates technical debt and chaotic code. Developers usually fall into one of two traps:

  1. Delegate too much. Fall into a mindless generative flow, creating spaghetti code.
  2. Delegate nothing. Fear AI, keep everything in their head, and quickly burn out.

We propose an engineering path—a balanced working model where AI becomes a predictable tool, not a chaotic generator.

Course Program: From "Vibe-Coder" to AI‑Hero

In 2 weeks, you will go from chaotic requests to systematic automation. The program is divided into logical modules:

Course Modules

  • Pre-course: Rapid immersion into Claude Code, basics of LLM and the Explore/Build/Clear cycle.
  • Context Management: Working with configuration (AGENTS.md), custom skills, and targeted content delivery.
  • Architecture and Planning: PRD, multi-step plans, tracer bullets for solution testing.
  • Feedback Loops: How to build a constraint system ensuring the quality of output code.
  • Autonomous Work (AFK): Launching agents through Ralph loops with progress monitoring.
  • Product Design: How to combine research, prototyping, and engineering practices for mature IT solutions.

What will change in your work?

Before the Course

  • "YOLO" mode and chaotic code generation.
  • Confused codebase without architecture.
  • Either hundreds of useless tests or none at all.
  • Loss of understanding of one's own system.
  • AI that needs constant oversight.

After the Course

  • Sandboxes, constraints, and predictability of AI behavior.
  • Architecturally clean codebase with deep structure.
  • Testing at key boundaries of the system.
  • Control of structure and logic without overload.
  • A reliable AI agent to whom tasks can be delegated.

Why This Methodology Works

Engineering is a mindset, not an IDE. Tools change, but the foundation remains: communication, decomposition, systematic planning, and skill in managing complexity. These skills are equally effectively applied to working with both people and AI agents.

The Author's Personal Experience

Using Claude Code and established automation cycles, I single-handedly created a professional video editor and CMS on TypeScript/Effect.ts—over 1000 commits and 500+ tasks without sacrificing work and personal life.

Now, I want to share this superpower with you.

Who teaches AI Coding for Real Engineers? Matt Pocock

Matt Pocock thumbnail

Matt Pocock is a UK-based developer and the founder of Total TypeScript — one of the most authoritative paid course platforms on the TypeScript language. He was previously a developer-experience engineer at Vercel and is widely cited as one of the clearest teachers of TypeScript's deeper type-system patterns. His Twitter / X presence is one of the largest single-language educational accounts in the JavaScript ecosystem.

His CourseFlix listing carries four Matt Pocock courses: Total TypeScript — Professional TypeScript Training (the platform's flagship comprehensive course), TypeScript Pro Essentials, AI SDK v5 Crash Course, and Build Your Own AI Personal Assistant in TypeScript. The TypeScript material is taught at the level of a working senior engineer who routinely uses the type system as a design tool, not just type annotations.

Material is paid; Total TypeScript runs on per-course pricing on the original platform. Courses are aimed at intermediate-and-up TypeScript developers.

What lessons are included in AI Coding for Real Engineers?

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#1: 001 Where We're Going Before We Start
All Course Lessons (92)
#Lesson TitleDurationAccess
1
001 Where We're Going Before We Start Demo
03:55
2
002 Navigating The Discord Before We Start
03:03
3
003 Repo Setup Before We Start
03:28
4
004 Database Migrations Before We Start
03:40
5
005 Setting Up Claude For The Course Before We Start
02:56
6
006 How To Take This Course Before We Start
06:09
7
007 Office Hours Before We Start
00:57
8
008 Intro Getting To Know Claude Code
00:49
9
009 Managing Your Claude Code Session Getting To Know Claude Code
04:07
10
010 Prompting In The Terminal Getting To Know Claude Code
02:26
11
011 Claude And Your IDE Getting To Know Claude Code
01:58
12
012 Going Forwards And Backwards In Time Getting To Know Claude Code
03:05
13
013 Running Bash Commands Getting To Know Claude Code
03:47
14
014 Permissions Getting To Know Claude Code
04:16
15
015 The Constraints Of LLMs Day 1 Fundamentals
08:12
16
016 What Are Subagents Day 1 Fundamentals
02:32
17
017 Codebase Exploration Day 1 Fundamentals
01:32
18
018 Codebase Exploration Solution
02:47
19
019 Build A Feature Day 1 Fundamentals
02:02
20
020 Build A Feature Solution
08:11
21
021 Non Determinism Day 1 Fundamentals
01:44
22
022 Showing Context In The Status Line Day 1 Fundamentals
03:36
23
023 Why Plan Mode Sucks Day 1 Fundamentals
05:04
24
024 The Grill Execute Clear Loop Day 1 Fundamentals
01:53
25
025 The Grill Execute Clear Loop solution
09:24
26
026 Compaction Day 1 Fundamentals
07:57
27
027 Handing Off Day 1 Fundamentals
03:31
28
028 What Is An Agents MD File Day 2 Steering
06:23
29
029 Steering An Agent With The Agents MD File Day 2 Steering
02:20
30
030 Steering An Agent With The Agents MD File Solution
03:36
31
031 Progressive Disclosure Day 2 Steering
03:18
32
032 What Are Agent Skills Day 2 Steering
06:58
33
033 Using Skills For Steering Day 2 Steering
01:46
34
034 Using Skills For Steering Solutions
04:20
35
035 Automatic Memory Day 2 Steering
02:13
36
036 How To Tackle Massive Tasks Day 3 Planning
03:19
37
037 Write Great PRDs With This Skill Day 3 Planning
02:42
38
038 Write Great PRDs With This Skill Solution
11:20
39
039 Split Features Across Multiple Context Windows With Multi Phase Plans Day 3 Planning
00:59
40
040 Split Features Across Multiple Context Windows With Multi Phase Plans Solution
03:40
41
041 What Are Tracer Bullets Day 3 Planning
03:10
42
042 Use Tracer Bullets In Our Multi Phase Plan Day 3 Planning
01:10
43
043 Use Tracer Bullets In Our Multi Phase Plan Solution
03:56
44
044 Executing Our Multi Phase Plan Day 3 Planning
01:22
45
045 Executing Our Multi Phase Plan Solution
06:36
46
046 Ask User Question Day 3 Planning
01:47
47
047 AI Coding for Real Engineers Office Hours (Day 1 Morning)
49:41
48
048 AI Coding for Real Engineers Office Hours (Day 1 Afternoon)
44:56
49
049 Is Code Cheap Day 4 Feedback Loops
06:05
50
050 Steering Agents To Use Feedback Loops With Skills Day 4 Feedback Loops
03:21
51
051 Building A Do Work Skill Day 4 Feedback Loops
00:46
52
052 Building A Do Work Skill Solution
03:06
53
053 Using Our Do Work Skill Day 4 Feedback Loops
01:06
54
054 Using Our Do Work Skill Solution
03:03
55
055 Fixing Agents Broken Formatting With Pre Commit Day 4 Feedback Loops
03:52
56
056 What Is Red Green Refactor Day 4 Feedback Loops
03:43
57
057 Red Green Refactor Day 4 Feedback Loops
01:35
58
058 Red Green Refactor Solution
04:30
59
059 What Is An AFK Agent Day 5 AFK Agents
02:25
60
060 Sandcastle Day 5 AFK Agents
01:56
61
061 Trying HITL Agents Day 5 AFK Agents
03:54
62
062 Trying HITL Agents Solution
01:35
63
063 Sandboxing Day 5 AFK Agents
04:53
64
064 Setting Up And Trying AFK Agents Day 5 AFK Agents
02:30
65
065 Setting Up And Trying AFK Agents Solution
03:27
66
066 Using Backlogs To Queue Tasks For AFK Agents Day 5 AFK Agents
03:24
67
067 Setting Up Our Repo For GitHub Issues Day 5 AFK Agents
01:19
68
068 Hooking Up Agents To Your Backlog Day 5 AFK Agents
03:15
69
069 Hooking Up Agents To Your Backlog Solution
02:29
70
070 Updating Our PRD And Plan Skill To Use GitHub Day 5 AFK Agents
01:32
71
071 HITL And AFK Tasks Day 6 Human In The Loop Patterns
02:06
72
072 Dont Plan Kanban Day 6 Human In The Loop Patterns
04:38
73
073 Using The Kanban Skill Day 6 Human In The Loop Patterns
01:09
74
074 Using The Kanban Skill Solution
05:24
75
075 Research Day 6 Human In The Loop Patterns
03:14
76
076 Trying Out Research Day 6 Human In The Loop Patterns
01:46
77
077 Trying Out Research Solution
04:27
78
078 Prototyping Day 6 Human In The Loop Patterns
02:57
79
079 Trying Out UI Prototyping Day 6 Human In The Loop Patterns
01:35
80
080 Trying Out UI Prototyping Solution
03:14
81
081 The Prototype Skill Day 6 Human In The Loop Patterns
02:15
82
082 Designing Codebases Ai Loves Day 6 Human In The Loop Patterns
07:31
83
083 The Improve Codebase Architecture Skill Day 6 Human In The Loop Patterns
02:22
84
084 The Improve Codebase Architecture Skill Solution
04:57
85
085 Adding Module Awareness To Our Planprd Skill Day 6 Human In The Loop Patterns
01:53
86
086 The Final Workflow Day 6 Human In The Loop Patterns
02:26
87
087 Appendix Greenfield Projects Day 6 Human In The Loop Patterns
04:43
88
088 Appendix grill-with-docs Day 6 Human In The Loop Patterns
07:07
89
089 Office Hours - Day 6 Morning
49:29
90
090 Office Hours - Day 6 Afternoon
48:21
91
091 Final Office Hours - Morning
53:46
92
092 Final Office Hours - Afternoon
52:26
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Frequently asked questions

What are the prerequisites for this course?
The course is designed for developers with basic knowledge of AI tools. Familiarity with Claude Code and general programming concepts will be beneficial. The pre-course module offers a rapid immersion into Claude Code, LLM basics, and the Explore/Build/Clear cycle, ensuring students start with a solid foundation.
What projects or skills will I build during this course?
Throughout the course, students will engage in building features, managing context through AGENTS.md, writing PRDs, and using tracer bullets for solution testing. Skills such as building a constraint system for code quality and launching autonomous AFK agents will also be developed.
Who is the target audience for this course?
This course is aimed at developers who are looking to integrate AI tools into production environments effectively. It is particularly suited for those who want to transition from chaotic request handling to systematic automation using AI.
How does this course compare in depth to similar AI courses?
Unlike other AI courses that might focus on theoretical aspects, this course emphasizes practical implementation in production environments. It covers a range of topics from context management and architectural planning to feedback loops and autonomous work, providing a hands-on, structured approach.
What specific tools and platforms will I learn about in this course?
The course focuses on using Claude Code within various development environments. Students will learn about managing sessions, prompting in the terminal, and integrating AI with IDEs. Additionally, it covers using Bash commands and setting up configurations with AGENTS.md files.
What is not covered in this course?
The course does not cover the basics of general programming or machine learning from scratch. It assumes a working knowledge of AI concepts and is focused on applying AI tools in engineering contexts rather than teaching foundational AI theories.
What is the time commitment required for this course?
This is a two-week intensive course, with a total of 92 lessons. It is designed to be immersive, requiring a significant time commitment over a short period to ensure comprehensive coverage of AI integration in production.