CourseFlix

Understanding AI-Assisted Development

3h 18m 12s
English
Paid

Welcome to a new era of software development where integrating artificial intelligence is no longer a futuristic concept, but a fundamental necessity. This course, focused on mindful software development using AI, challenges the prevalent notions in the developer community. While some fear losing their skills to machines, others misuse AI tools without understanding, hoping for positive outcomes. Here, we propose a third path: AI not as a replacement for understanding, but as an enhancer, capable of both creating order and chaos without the right approach.

Embracing AI with Strategic Thinking

Today’s critical skill is not simply knowing how to "use AI," but the ability to think in tandem with it. Rather than anchoring learning to transient tools or models, this course offers a robust framework that explains the functioning of large language models (LLMs). You will learn to implement strategic, reproducible development processes that go beyond mere technical usage.

Foundations of Large Language Models

  • Vector Representations: Understanding the mathematical foundations.
  • Attention Mechanisms: Delving into how models prioritize information.
  • Model Limitations: Exploring linguistic and probabilistic boundaries.
  • AI "Hallucinations": Identifying and managing misleading outputs.

Contextual Engineering

Our focus on contextual engineering will equip you to manage not just how questions are posed to the AI, but what underlying information the model considers relevant. This understanding is pivotal in developing effective AI-assisted workflows for planning, implementation, debugging, code review, and integrating AI into all phases of software development.

Target Audience and Outcomes

This course is designed for both beginner developers seeking to harness AI while gaining comprehensive skills, and experienced engineers and team leads aiming to incorporate AI into team workflows without sacrificing quality and discipline. We also dive into the risks associated with AI dependency and strategies to leverage AI as a tool for enhancing expertise rather than becoming overly reliant on it as a substitute.

What You Will Achieve

By the end of this course, you will move away from randomness in development, gaining clarity, confidence, and a deeper understanding of AI collaboration in real-world production environments. In our AI-driven world, true success belongs to those who understand the processes behind AI, rather than those simply searching for the best prompts.

Additional

EARLY ACCESS

About the Author: Anthony Alicea

Anthony Alicea thumbnail

Anthony Alicea is a US software engineer and educator best known for JavaScript: Understanding the Weird Parts — one of the canonical paid courses on JavaScript's underlying mental model (execution context, scope chain, prototype inheritance, the call stack) and one of the most widely-recommended deep-dives into the language for developers ready to move past surface syntax.

The course catalog extends into TypeScript (the deep type-system material rather than the syntax tour), React, Node.js, and the broader JavaScript ecosystem. The teaching style is unusually rigorous about the language fundamentals — Anthony's courses are taught at the level of someone who wants you to understand why JavaScript behaves the way it does, not just memorise the rules.

The CourseFlix listing under this source carries 7 Anthony Alicea courses spanning that range. Material is paid and aimed at developers ready to deepen their craft on the JavaScript / TypeScript stack.

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#1: 1. Introduction
All Course Lessons (65)
#Lesson TitleDurationAccess
1
1. Introduction Demo
01:42
2
2. Setup
01:02
3
3. A Proper Mental Model of LLMs
01:32
4
4. Large Language Models and Grammar
11:25
5
5. Conceptual Aside Vectors
04:22
6
6. Attention and Attending
04:44
7
7. Conceptual Aside Determinism vs Non-Determinism
03:13
8
8. Determinism and the Digital Age
02:14
9
9. Conceptual Aside Programming Language Grammar
01:53
10
10. Prediction and Statistics
07:07
11
11. Confabulation and Unreliability
04:14
12
12. Conceptual Aside Reasoning Models
02:34
13
13. Conceptual Aside Agents
01:59
14
14. You Aren't Having a Conversation (and the Dangers of Anthropomorphization)
03:25
15
15. Context Engineering and Management
00:25
16
16. Pattern Matching and Navigating the Embedding Space
02:02
17
17. Is It Engineering
02:41
18
18. Project Context
04:04
19
19. Technical Context
02:05
20
20. Context Refresh and Drift
04:28
21
21. Immediate Context
02:46
22
22. Task Context
02:39
23
23. Clean Human Code
02:49
24
24. Agents and Context
02:13
25
25. Prompt Engineering
00:57
26
26. The Anatomy of Effective Prompts
03:08
27
27. Decomposition
03:29
28
28. Roles and Personas
01:57
29
29. Specificity and Constraints
02:18
30
30. Examples of Expected Behavior
02:17
31
31. Session Context
01:49
32
32. Code Generation Workflows Planning
00:33
33
33. Brainstorming
05:32
34
34. Business Rules and Constraints
02:00
35
35. Documentation
09:33
36
36. Implementation Planning
10:41
37
37. The Context Problem
00:25
38
38. Conceptual Aside Context Window
01:50
39
39. Window Size
01:44
40
40. Conceptual Aside System Prompt
04:43
41
41. Context Rot
01:57
42
42. Conceptual Aside Markdown
01:54
43
43. Skills
00:20
44
44. The Anatomy of a Skill
02:30
45
45. Frontmatter
04:07
46
46. Instructions
03:06
47
47. Scripts
03:36
48
48. Assets
02:06
49
49. How Agents Integrate Skills
00:37
50
50. Conceptual Aside Progressive Disclosure
01:12
51
51. Discover
02:21
52
52. Load Metadata
03:13
53
53. Match Tasks to Skills
04:12
54
54. Activate
02:14
55
55. Execute and Access
05:26
56
56. Skills In Action
04:12
57
57. Skill Authoring
00:21
58
58. Metadata
02:33
59
59. Good Context
01:47
60
60. Domain Expertise
01:48
61
61. New Capabilities
01:52
62
62. Repeatable Workflows
11:34
63
63. Interoperability
01:47
64
64. Finding Pre-Existing Skills
01:14
65
65. Skills Project
01:39
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Course content

65 lessons · 3h 18m 12s
Show all 65 lessons
  1. 1 1. Introduction 01:42
  2. 2 2. Setup 01:02
  3. 3 3. A Proper Mental Model of LLMs 01:32
  4. 4 4. Large Language Models and Grammar 11:25
  5. 5 5. Conceptual Aside Vectors 04:22
  6. 6 6. Attention and Attending 04:44
  7. 7 7. Conceptual Aside Determinism vs Non-Determinism 03:13
  8. 8 8. Determinism and the Digital Age 02:14
  9. 9 9. Conceptual Aside Programming Language Grammar 01:53
  10. 10 10. Prediction and Statistics 07:07
  11. 11 11. Confabulation and Unreliability 04:14
  12. 12 12. Conceptual Aside Reasoning Models 02:34
  13. 13 13. Conceptual Aside Agents 01:59
  14. 14 14. You Aren't Having a Conversation (and the Dangers of Anthropomorphization) 03:25
  15. 15 15. Context Engineering and Management 00:25
  16. 16 16. Pattern Matching and Navigating the Embedding Space 02:02
  17. 17 17. Is It Engineering 02:41
  18. 18 18. Project Context 04:04
  19. 19 19. Technical Context 02:05
  20. 20 20. Context Refresh and Drift 04:28
  21. 21 21. Immediate Context 02:46
  22. 22 22. Task Context 02:39
  23. 23 23. Clean Human Code 02:49
  24. 24 24. Agents and Context 02:13
  25. 25 25. Prompt Engineering 00:57
  26. 26 26. The Anatomy of Effective Prompts 03:08
  27. 27 27. Decomposition 03:29
  28. 28 28. Roles and Personas 01:57
  29. 29 29. Specificity and Constraints 02:18
  30. 30 30. Examples of Expected Behavior 02:17
  31. 31 31. Session Context 01:49
  32. 32 32. Code Generation Workflows Planning 00:33
  33. 33 33. Brainstorming 05:32
  34. 34 34. Business Rules and Constraints 02:00
  35. 35 35. Documentation 09:33
  36. 36 36. Implementation Planning 10:41
  37. 37 37. The Context Problem 00:25
  38. 38 38. Conceptual Aside Context Window 01:50
  39. 39 39. Window Size 01:44
  40. 40 40. Conceptual Aside System Prompt 04:43
  41. 41 41. Context Rot 01:57
  42. 42 42. Conceptual Aside Markdown 01:54
  43. 43 43. Skills 00:20
  44. 44 44. The Anatomy of a Skill 02:30
  45. 45 45. Frontmatter 04:07
  46. 46 46. Instructions 03:06
  47. 47 47. Scripts 03:36
  48. 48 48. Assets 02:06
  49. 49 49. How Agents Integrate Skills 00:37
  50. 50 50. Conceptual Aside Progressive Disclosure 01:12
  51. 51 51. Discover 02:21
  52. 52 52. Load Metadata 03:13
  53. 53 53. Match Tasks to Skills 04:12
  54. 54 54. Activate 02:14
  55. 55 55. Execute and Access 05:26
  56. 56 56. Skills In Action 04:12
  57. 57 57. Skill Authoring 00:21
  58. 58 58. Metadata 02:33
  59. 59 59. Good Context 01:47
  60. 60 60. Domain Expertise 01:48
  61. 61 61. New Capabilities 01:52
  62. 62 62. Repeatable Workflows 11:34
  63. 63 63. Interoperability 01:47
  64. 64 64. Finding Pre-Existing Skills 01:14
  65. 65 65. Skills Project 01:39

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Frequently asked questions

What is Understanding AI-Assisted Development about?
Welcome to a new era of software development where integrating artificial intelligence is no longer a futuristic concept, but a fundamental necessity. This course, focused on mindful software development using AI, challenges the prevalent…
Who teaches Understanding AI-Assisted Development?
Understanding AI-Assisted Development is taught by Anthony Alicea. You can find more courses by this instructor on the corresponding source page.
How long is Understanding AI-Assisted Development?
Understanding AI-Assisted Development contains 65 lessons with a total runtime of 3 hours 18 minutes. All lessons are available to watch online at your own pace.
Is Understanding AI-Assisted Development free to watch?
Understanding AI-Assisted Development is part of CourseFlix's premium catalog. A CourseFlix subscription unlocks the full video player; the course description, table of contents, and preview information are available to everyone.
Where can I watch Understanding AI-Assisted Development online?
Understanding AI-Assisted Development is available to watch online on CourseFlix at https://courseflix.net/course/understanding-ai-assisted-development. The page hosts every lesson with the integrated video player; no download is required.