AI coding agents can produce working code at remarkable speed, but speed without explicit intent, constraints, and verification can quickly turn into inconsistency and risk. As software development moves from deterministic code toward probabilistic agentic systems, the developer’s role changes from writing every implementation detail to defining what agents may build, how they should behave, and how their work will be verified.

In this practical session, we introduce Spec-Driven AI Engineering as a way to make that shift manageable. We examine how specifications become a shared source of truth for humans and coding agents, how Spec Kit turns intent into requirements, plans, and tasks, and how guardrails for resilience, observability, security, and testing keep agent-generated systems under control. We also connect these ideas to Microsoft Agent Framework and MCP, explaining how developers can build and govern their own agents and tools rather than only consume them.

You will leave with a clearer model for directing coding agents, structuring their context, and moving from fast experimentation toward reliable engineering.

Format: Technical lecture with slides and practical examples. Suitable for a 45–60 minute conference session, with optional Q&A.

Target audience: Software developers, AI engineers, architects, and technical leads working with coding agents or agentic systems.

Level: Intermediate (Level 200). Basic familiarity with software development and generative AI is helpful.

First public delivery: GeekAcademy 2026, April 13, 2026.

Technical requirements: A projector or large screen suitable for displaying slides and code clearly.