AI-driven Product Development

AI-driven product development isn’t about prompting faster — it’s about building right. Magnus Axelqvist and Björn Wismén teach a disciplined engineering practice where AI accelerates delivery capability without accelerating technical debt — tailored to your organisation, your tools, and your codebase.

We adapt depth, pace, and examples to your team and deliver the training when, where, and for however many people you need.

We cover, among other things

• Reasoning and specifying correctly before writing code — and why this is the most important step
• Configuring AI roles with clear responsibilities for product strategy, design, implementation, and testing
• Building an instruction hierarchy that codifies your team’s standards so AI follows them automatically — across sessions and team members
• Using TDD, static type checking, and linting as an evaluation chain for AI-generated code
• Setting up agentic workflows with built-in quality control — delegation, autonomous code review cycles, and tool access
• Managing project context over time with state files, structured memory, and retro-based improvement
• Combining feature slicing, trunk-based development, and continuous delivery with AI at high pace
• Identifying and avoiding the most common anti-patterns in AI-driven development

Prerequisites

Participants need some practical experience writing code — this is not an introduction to programming. Experience with AI coding tools (Cursor, Claude Code, Copilot or similar) is a plus, but not required.