Recently I’ve seen many blog posts and videos about AI coding workflows — how people build them, how productive they are, and often a mention that a course is available (or coming soon) to teach the same system.
I think it’s great that people share their knowledge and experience with fellow developers.
At the same time, I believe much of this knowledge is not that hard to obtain on your own, especially given how powerful modern AI tools are for learning.
Before buying a course, it may be worth trying to explore the topic yourself first.
My approach
When I want to quickly understand a new topic, I often use a “Fisherman’s prompt” — a prompt template designed to generate structured learning paths.
You can find the template here:
https://gist.github.com/disler/cad56b41fb614a4e394f7b719bca5273
(There is a lot of great material in that repository.)
For example, here is a prompt I used to explore AI-augmented coding workflows:
I'm a Senior software Engineer and I want to learn AI augmented coding so I can utilize Open Claude to help me with engineering. Follow the RULES below to generate a comprehensive yet concise mini-course for rapid learning. The course should contain chapters that teach me about these SUB_TOPICS. Make sure the chapters fit my level, profession and topic. Ask for clarification if you need more information about my knowledge.
SUB_TOPICS
- Mental Models of LLMs for Engineers
- Effective Claude Code Usage for Software Development
- Context Engineering (efficient context management)
- Task Decomposition for AI Agents
- Designing Agent Skills (Markdown capability files)
- Sub-agents and Task Delegation
- Agent Loops (ReAct / Reflection / Self-correction)
RULES
- Use concrete examples to explain every concept
- Use emojis to add expression
- Generate one chapter at a time
- Ask for feedback at the end of each chapter
- Ask if I need clarification at the end of each chapter
- With each concept, explain real world use cases
- After we complete every sub topic, present a list of additional topics we can explore that align with my level, profession, topic and objective.
You can also adjust the topic list depending on what interests you most.
Using the generated course as a starting point, together with resources like the Anthropic skills repository, https://github.com/anthropics/skills/blob/main/skills/skill-creator/SKILL.md
gives you a very fast way to get hands-on experience.
From there, experiment with workflows that work for you, iterate on them, and refine your approach.
After that, you’ll have a much clearer understanding of the field — and you’ll know whether you actually need a course or not.
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