English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 103 Lessons (12h 41m) | 5.87 GB
AI-Powered Software Engineering and Automation. Master AI agents, prompts, and automated workflows with cutting-edge generative AI tools.
What you’ll learn
- Develop Python-based agents that independently process data, analyze documents, and execute complex multi-step workflows without human intervention.
- Orchestrate Claude Code agents to develop software in minutes, managing parallel development streams across multiple git branches simultaneously.
- Engineer sophisticated prompts and build specialized GPTs that understand business contexts and automate domain-specific professional tasks.
Skills you’ll gain
- Multimodal Prompts
- Software Engineering
- Generative AI Agents
- Agentic systems
- Prompt Patterns
- Automation
- Software Architecture
- Software Testing
- Software Development Tools
- LLM Application
- Software Design
- Software Development
- Artificial Intelligence and Machine Learning (AI/ML)
- Productivity
- AI Personalization
Tools you’ll learn
- ChatGPT
- Prompt Engineering
- Generative AI
- Anthropic Claude
- OpenAI
Transform from Code Writer to AI Orchestrator in 4 Comprehensive Courses
The software engineering landscape has fundamentally shifted. While others debate whether AI will replace developers, you’ll learn to amplify your capabilities by 1000X through strategic AI partnership. This specialization teaches you to think beyond traditional coding—you’ll orchestrate AI agents that build entire applications in minutes, manage parallel development streams, and solve complex problems autonomously.
What You’ll Achieve
Build production software at unprecedented speed — Watch Claude Code construct full-stack applications with databases, APIs, and user interfaces while you focus on architecture and strategy
Command AI agents that think and act independently — Deploy Python-powered agents that analyze requirements, write code, run tests, and integrate features across multiple git branches simultaneously
Deploy custom AI assistants for real business problems — Create specialized GPTs that understand your company policies, process expense reports, analyze legal documents, and handle complex workflows with human-like intelligence
This isn’t about learning to use AI tools—it’s about fundamentally reimagining how complex work gets done. You’ll graduate with frameworks, like Claude Code and OpenAI GPTs, that remain valuable regardless of which AI technologies dominate tomorrow, because you’ll understand the underlying principles of human-AI collaboration at the deepest level.
Applied Learning Project
Throughout the specialization, learners will progressively build an integrated AI-powered business automation system—starting with Claude Code to rapidly prototype applications, then developing Python agents that autonomously handle complex workflows like document analysis and data processing, engineering sophisticated prompts that enable precise AI reasoning across domains, and finally deploying custom GPTs that serve as intelligent interfaces for end users. All projects are hands-on experiences with state-of-the-art generative AI tools, ensuring learners gain practical expertise with the same cutting-edge technologies reshaping industries today.
Table of Contents
ai-agents-python
agentic-ai-concepts
untitled-lesson
1 introduction
2 flipped-interaction-pattern
3 the-agent-loop
4 running-the-code-samples-in-the-course_instructions
5 try-out-programmatic-prompting_instructions
6 try-out-the-customer-service-agent_instructions
7 adding-structure-to-ai-agent-outputs
8 learning-more-staying-connected_instructions
ai-agents-tools-actions-language
untitled-lesson
9 gail-goals-actions-information-language
10 giving-agents-tools
11 tool-descriptions-and-naming
12 tool-results-and-agent-feedback
13 try-out-an-agent-that-calls-python-functions_instructions
14 try-out-llm-function-calling_instructions
15 try-out-an-agent-loop-with-function-calling_instructions
16 exercise-extend-the-function-calling-agent_instructions
game-a-conceptual-framework-for-ai-agents
untitled-lesson
17 overview-of-the-game-framework
18 simulating-agents-in-chatgpt
19 try-out-the-agent-framework_instructions
agent-tool-mangement
untitled-lesson
20 try-out-the-readme-agent-with-the-decorator_instructions
rethinking-how-software-is-built-in-the-age-of-ai-agents
untitled-lesson
21 build-the-impossible-with-ai-agents
22 rethinking-how-we-teach-innovation
23 hallucination-is-a-new-form-of-computing
24 new-ways-to-access-and-extract-information
claude-code
scaling-up-software-engineering-with-claude-code-generative-ai
untitled-lesson
25 introduction-to-claude-code-software-engineering-with-ai-agents
26 x-improvement-in-software-engineering-productivity-with-big-prompts
27 an-important-note-on-costs_instructions
28 exercise-getting-started-with-claude-code-building-your-first-application_instructions
29 learning-more-staying-connected_instructions
leveraging-the-software-engineering-advantages-of-claude-code
untitled-lesson
30 one-software-engineer-to-another-lets-talk-about-the-fear
31 ai-labor-claude-code-is-an-ai-development-team
32 the-best-of-n-pattern-leverage-ai-labor-cost-advantages
33 exercise-build-multiple-versions-of-a-feature-with-best-of-n_instructions
generative-ai-claude-code-code-quality
untitled-lesson
34 can-ai-judge-code-quality
35 exercise-ai-evaluation-of-code-feature-implementations_instructions
36 does-ai-labor-understand-design-principles
37 chat-craft-scale-spend-more-time-designing-innovating
38 chat-craft-and-explore-requirements-options
39 chat-rapid-prototyping-personas
40 craft-constraints-prompts-for-claude-code
building-process-context-in-claude-code
untitled-lesson
41 global-persistent-context-claude-md
42 writing-claude-md-files_instructions
43 reusable-targeted-context-process-claude-code-commands
44 creating-claude-commands_instructions
45 in-context-learning-teaching-with-examples
46 exercise-building-a-documentation-generator_instructions
47 contribute-help-build-a-curated-resource-of-great-commands-claude-md-etc_instructions
version-control-parallel-development-with-claude-code
untitled-lesson
48 claude-code-version-control-git-branches
49 allowing-claude-code-to-work-in-parallel-with-git-worktrees_instructions
50 claude-subagents-tasks_instructions
51 parallel-feature-development-with-subagents-tasks-and-git-worktrees_instructions
improving-claude-code-scalability-reasoning
untitled-lesson
52 being-claude-codes-hands-eyes-and-ears
53 ensuring-claude-code-checks-its-own-work
54 software-design-token-limits-and-maintainability
55 having-claude-code-think-plan-first_instructions
56 project-structure-and-file-naming-is-critical-context-for-claude-code
multimodal-prompting-process
untitled-lesson
57 exercise-from-coffee-stained-napkin-to-production-code-with-multimodal-prompting_instructions
58 start-by-fixing-the-process-context-not-the-code
openai-custom-gpts
custom-gpts-fundamentals
untitled-lesson
59 welcome
60 programming-a-gpt
61 custom-instructions
62 retrieval-augmented-generation
63 putting-it-all-together-custom-gpts
64 understanding-how-gpts-use-tools
65 capital-a-framework-for-customizing-how-chatbots-converse_instructions
66 building-a-persona-for-your-custom-gpt
67 prompt-patterns_instructions
68 format-of-the-persona-pattern_instructions
69 learning-more-staying-connected_instructions
think-create-great-gpts-part-i
test
70 test
71 build-a-benchmark
72 benchmark-design-considerations_instructions
73 build-a-custom-gpt-for-generating-test-cases
help-the-user-solve-the-problem-not-provide-answers
74 the-goal-is-to-help-the-human-solve-the-problem-not-provide-the-answer
75 how-to-cite-knowledge
76 output-formatting
77 template-pattern-markdown_instructions
78 provide-the-facts
79 hedging-while-helping
80 menu-action-pattern
81 format-of-the-menu-actions-pattern_instructions
82 where-to-get-additional-help
information-before-decision-making
83 information-before-decision-making
84 flipped-interaction-pattern
85 format-of-the-flipped-interaction-pattern_instructions
86 missing-context-from-the-user
87 user-customized-experiences
think-create-great-gpts-part-ii
never-assume
88 boundaries
89 how-to-respond-to-the-absence-of-knowledge
90 combating-ambiguity-in-user-prompts-with-question-refinement
91 format-of-the-question-refinement-pattern_instructions
92 enforcing-boundaries-still-helping-with-the-alternative-approaches-pattern
93 format-of-the-alternative-approaches-pattern_instructions
94 cognitive-verifier-pattern
95 format-of-the-cognitive-verifier-pattern_instructions
knowledge-must-be-clear
96 handling-ambiguity-in-concept-mapping
97 knowledge-conflict-resolution
wrapping-up
98 you-and-your-business-are-responsible-not-the-bot
99 adversarial-testing
100 wrapping-up
prompt-engineering
course-introduction
course-overview
101 motivating-example-building-a-meal-plan-with-a-fusion-of-food-from-ethiopia-and
102 overview-of-the-course
103 motivating-example-act-as-a-speech-pathologist
104 setting-up-an-account-and-using-chatgpt_instructions
large-language-model-basics
105 what-are-large-language-models
106 randomness-in-output
introduction-to-prompts
what-are-prompts
107 what-is-a-prompt
108 intuition-behind-prompts
109 everyone-can-program-with-prompts
intro-to-prompt-patterns
110 prompt-patterns
111 the-persona-pattern
112 reading-a-prompt-pattern_instructions
113 format-of-the-persona-pattern_instructions
114 learn-more-about-prompt-patterns_instructions
115 staying-connected-learning-more_instructions
prompts-conversations-new-information
116 introducing-new-information-to-the-large-language-model
117 prompt-size-limitations
118 prompts-are-a-tool-for-repeated-use
119 root-prompts
120 what-to-take-after-or-with-this-course_instructions
prompt-patterns-i
introduction-to-prompt-patterns
121 question-refinement-pattern
122 format-of-the-question-refinement-pattern_instructions
123 cognitive-verifier-pattern
124 format-of-the-cognitive-verifier-pattern_instructions
125 audience-persona-pattern
126 format-of-the-audience-persona-pattern_instructions
127 flipped-interaction-pattern
128 format-of-the-flipped-interaction-pattern_instructions
few-shot-examples
effective-prompts
129 few-shot-examples
130 few-shot-examples-for-actions
131 few-shot-examples-with-intermediate-steps
132 writing-effective-few-shot-examples
133 chain-of-thought-prompting
134 learn-more-about-chain-of-thought-prompting_instructions
135 react-prompting
136 learn-more-about-react_instructions
137 using-large-language-models-to-grade-each-other
prompt-patterns-ii
prompt-patterns-catalog
138 game-play-pattern
139 format-of-the-game-play-pattern_instructions
140 template-pattern
141 format-of-the-template-pattern_instructions
142 meta-language-creation-pattern
143 format-of-the-meta-language-creation-pattern_instructions
144 recipe-pattern
145 format-of-the-recipe-pattern_instructions
146 alternative-approaches-pattern
147 format-of-the-alternative-approaches-pattern_instructions
prompt-patterns-iii
prompt-patterns-catalog
148 ask-for-input-pattern
149 format-of-the-ask-for-input-pattern_instructions
150 combining-patterns
151 outline-expansion-pattern
152 format-of-the-outline-expansion-pattern_instructions
153 menu-actions-pattern
154 format-of-the-menu-actions-pattern_instructions
155 fact-check-list-pattern
156 format-of-the-fact-check-list-pattern_instructions
157 tail-generation-pattern
158 tail-generation-pattern_instructions
159 semantic-filter-pattern
160 format-of-the-semantic-filter-pattern_instructions
161 course-conclusion-thank-you
162 continue-learning-about-prompt-engineering_instructions
163 continue-learning-about-prompt-engineering_jules
Resources
prompt-engineering-showcase
164 resources
chatgpt
165 resources
reading-materials-on-prompt-engineering
166 jules
167 resources
prompts-used-for-creating-the-emails
168 resources
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