Unit
AI Foundations for Tech Teams
AI Foundations for Tech Teams gives product, engineering, and delivery teams a practical understanding of how AI fits into modern software work. The course builds a shared baseline around core AI concepts, realistic use cases, delivery impact, engineering trade-offs, and AI limitations, helping teams make clearer decisions before moving into adoption, workflow design, or AI delivery.
What you'll learn
AI Fundamentals
- Explain core AI concepts and terminology relevant to software product and engineering teams
- Distinguish between AI capabilities and traditional software behaviors in product contexts
- Distinguish realistic AI use cases from common AI misconceptions in technical product development
AI in Product and Engineering
- Identify how AI influences product thinking and feature design decisions
- Explain how AI affects software delivery workflows
- Identify AI-related risks relevant to product and engineering teams
AI Adoption and Delivery
- Identify key decision points for adopting AI within technical delivery workflows
- Explain the shift from AI experimentation to more repeatable delivery practices
- Identify roles and responsibilities for AI adoption across product, engineering, and delivery teams
AI Impact on Engineering
- Explain how AI changes engineering trade-offs and technical decision-making
- Evaluate implications of AI integration on software quality, testing, and maintenance
- Explain how probabilistic AI outputs change assumptions about system behaviour and reliability
AI Suitability and Evaluation
- Identify criteria for assessing AI suitability in product and engineering contexts
- Explain how to assess AI output quality and reliability
- Recognise common AI failure modes in product and engineering contexts
Collaboration and Communication
- Identify practical AI literacy needs that support effective communication across technical roles
- Explain how to communicate AI limitations and uncertainty in product and engineering decisions
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