Understand AI’s evolving role in your profession – the landscape, not the implementation.
Course Introduction
For developers, QA, architects, and DevOps, this course maps where AI-assisted development genuinely helps versus where it quietly misleads. It weighs productivity against quality, surfaces security risks such as prompt injection and data leakage, and draws the line between what to delegate to AI and what to keep doing yourself. Attendees leave with realistic expectations and the vocabulary to discuss AI credibly with both teams and leadership.
Topics Covered
- The AI development landscape: what’s available, what works
- AI-assisted coding: where it helps, where it misleads
- Productivity vs. quality: understanding the trade-offs
- Security awareness: prompt injection, data leakage risks
- What to keep doing yourself vs. delegating to AI
Target Audience
- Developers
- QA
- Architects
- DevOps
What Attendees Leave With
- Understanding of AI tools in the development ecosystem
- Awareness of risks and limitations (security, quality)
- Realistic expectations for AI-assisted development
- Vocabulary to discuss AI with teams and leaders
Prerequisite Knowledge
A software development or engineering background (hands-on experience with the SDLC). No prior AI experience required.
Duration:
Half-Day
