← All courses
Coming soon
AI for Engineers
Use AI to reimagine how you work, not just to type faster.
Self-paced video courseIntermediate5 modules15 lessons
What you'll learn
- Where AI gives real leverage in software work, and where it doesn't
- Prompting and workflows that hold up on real codebases
- How to design, build and roll out an AI tool for your team
- Bringing AI into code review, planning and documentation
- Judging AI output: catching what it gets confidently wrong
- Changing how a team works, not just how one person types
Who it's for
Software engineers and tech leads who've tried AI tools and want to go further than autocomplete. You should be comfortable writing code. No machine learning background needed.
Curriculum
-
01
Leverage, not just speed
- Reimagining the work instead of accelerating it
- Finding the slowest, most repetitive parts of your week
- Picking problems where AI actually helps
-
02
Working with AI day to day
- Prompting for code, tests and reviews
- Giving models the right context
- Workflows I use every day
-
03
Building an AI tool for your team
- Case study: Chiku, an automated AI merge request reviewer
- From prototype to something people trust
- Measuring the impact: earlier bugs, faster reviews
-
04
Bringing your team along
- Rolling out alongside your day job
- Getting buy-in from senior engineers
- Keeping humans in the loop
-
05
Judgement and limits
- When not to use AI
- Checking output you didn't write
- Privacy, security and your codebase
About me
I'm Kuziwa, a self-taught engineer who worked at Amazon and now builds software in Johannesburg. I built Chiku, an AI merge request reviewer, and rolled it out alongside my day job. This course is everything I learned doing it.