justin/ai-workflow-course
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01 the copy paste problem 02 version control as a safety net 03 version control for words 04 getting the ai out of the browser 05 commit the ai config 06 branches sandboxes for experiments 07 worktrees running agents in parallel 08 remotes and hosting 09 issues and the task layer 10 reviewing code you didnt write 11 collaboration humans and agents 12 revert reset and recovery 13 testing in the ai era 14 continuous integration 15 security scanning 16 containers and reproducible environments 17 secrets config and environments 18 continuous delivery and deployment 19 runners the compute behind automation 20 mcp servers giving the ai hands 21 skills teaching the ai your playbook 22 securing third party mcp and skills 23 working with existing codebases 24 assistive agents 25 autonomous agents 26 orchestrating multiple agents 27 evals Home capstone
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claude edited this page 2026-06-22 18:48:55 -04:00

Generated from the ai-workflow-course repo • the model is the cheap, swappable part; the workflow is the durable skill.

📖 Home

Unit 1: Get out of the chat window

Unit 2: Make it shareable, reviewable, recoverable

Unit 3: Automate the checking and shipping

Unit 4: Extend the AI into your systems

Unit 5: AI in the Loop

Finale