Език: English
You ask an AI agent to build a product. It generates the interface, writes the backend, adds tests, and produces deployment configuration. Everything looks convincing. But who decided what the product should do, whether the architecture fits its constraints, or how the system should behave when something fails?
This talk examines the engineering decisions that remain essential when agents write the code. We’ll explore how missing requirements become assumptions, why passing tests don’t prove you built the right product, and what this means for design, deployment, and operations.
We’ll show how focused specifications, explicit constraints, and verifiable acceptance criteria guide agents toward useful results. We’ll also discuss why generating Rust code or infrastructure configuration does not give you the expertise to evaluate or operate it safely.
You’ll leave with a practical approach to guiding AI-assisted development and recognizing when plausible output still needs engineering judgment.
What attendees will learn
- Identify the product, design, and operational decisions hidden inside a request to “build this”
- Write focused specifications and project guidance that reduce ambiguous implementation choices
- Distinguish working code from a product that meets its requirements and operating constraints
- Evaluate agent-generated work across unfamiliar technologies and recognize when specialist review is needed
- Define acceptance criteria covering user behavior, failure handling, deployment, and recovery