This course pairs pragmatic agile method with AI-assisted engineering practice. Across five modules you trace the historical arc from waterfall to agile, internalize the playground-vs-plant mental model, learn root-cause analysis via the five-whys habit, sharpen technical communication and demos, structure project management with the lightest possible artifacts (Trello and spreadsheets over heavy tools), and apply AI workflows — diagram prompt engineering, summarization with Claude, AI pair programming, AWS CodeWhisperer for Rust, Bedrock-backed serverless architectures, RAG with Bedrock Knowledge Bases, and local speech-to-text with whisper.cpp. By the end you can adapt agile to your team rather than the other way around, recognize the anti-patterns that turn ceremonies into theater, and integrate AI tooling into a development loop that ships rather than just demos. Pragmatic, opinionated, and grounded in named patterns rather than methodology cargo-cult.

Agile With AI
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Recommended experience
What you'll learn
Adapt agile ceremonies to your team's actual workflow — drop the rituals that don't generate value, keep the ones that shorten feedback loops
Apply pragmatic project-management patterns using Trello and spreadsheets — small-batch work, lightweight artifacts, weekly cadence, blameless retros
Integrate AI workflows into engineering practice — diagram prompt engineering, summarization with Claude, AI pair programming
Recognize and avoid the project-management anti-patterns that produce ticket-shaped work and status theater
Skills you'll gain
- Technical Communication
- Agile Project Management
- Serverless Computing
- Software Development Methodologies
- Agile Methodology
- Artificial Intelligence
- Agile Product Development
- Sprint Retrospectives
- Devops Tools
- Agentic systems
- Automation
- DevOps
- Agile Software Development
- Software Design
- Test Automation
- Project Design
Tools you'll learn
Details to know

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April 2026
1 assignment
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There are 5 modules in this course
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