Provider
CXSense
AI Workflow Sprint
Enable your tech team to use AI safely, practically, and productively in real delivery work.
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