Course overview

AI has quickly become a central tool in software development, but in many organizations, the real productivity gains are missing. This is often referred to as The AI Effectiveness Gap.
This course focuses on how teams can work systematically with AI to increase deliverability, quality, and collaboration. Instead of ad-hoc use of AI, a role-based methodology is introduced where AI is integrated into the entire software lifecycle – from requirements and design to testing and operation.

Participants are given concrete ways of working to:

Create the right context for AI
Establish reproducible workflows
Reduce technical debt
Improve collaboration between technology and operations

The result is a more efficient and sustainable way of working where AI augments the team’s competence rather than replaces it.

Also check out our courses in data, cloud and AI to develop your knowledge in data analytics, cloud computing and artificial intelligence.

Course Objective

After the course you will be able to:

Identifying and Reducing The AI Effectiveness Gap
Use context engineering for better and more consistent AI results
Establish structured and secure AI workflows in teams
Use AI without creating technical debt or losing architectural control
Improve documentation using AI
Strengthen collaboration between technical and business-related roles

Target Group

The course is aimed at:

Software Developer
Technical leaders
Architects
Product Owner

Prerequisites

Experience in professional software development or technical leadership
Basic experience with AI tools such as ChatGPT, Claude, or GitHub Copilot

Certification

This course does not have any associated certification. Each participant who completes the course receives a course certificate.

Trainer

The course is delivered by experienced coaches with a background in agile transformation and modern software development.

More about the course

Course content

The AI Effectiveness Gap – Causes and Solutions
Context Engineering and Role-Based Collaboration
AI in the team’s workflow (requirements, development, testing, deployment)
Managing technical debt in AI-driven development
Human-in-the-loop – quality assurance and control
Build sustainable ways of working independently of AI model

Course overview

2 days

Basic

Can’t find a (suitable) date, but are interested in the course? Send in an expression of interest and we will do what we can to get an opportunity that suits.

För samtliga utbildningar gäller våra
Allmänna Villkor.

Company-adapted course

The course can be adapted from several perspectives:

Content and focus area
Scope of application
Structure

In collaboration with the course leader, we make sure that the course meets your wishes