Description
Spec-Driven Development: designing deterministic AI systems. This course explores how to move from writing simple AI prompts to a structured, industrial engineering workflow for designing deterministic, robust systems. This course, which incorporates the use of AI, teaches professionals how to move away from ad hoc prompt writing methods and toward a structured, production-standard engineering workflow. Rather than viewing AI as a simple code generator, this course teaches how to design systems in which technical documentation and specifications serve as the primary source of truth, architecture is shaped by defined goals, and validation is integrated into all phases of development. Spec-Driven Development (SDD) replaces trial-and-error approaches with a repeatable pipeline of specification, planning, tasking, implementation, and verification. By the end of this course, learners will learn how to manage AI-powered development in an auditable, scalable, and production-standards-aligned manner. The course explores why unstructured code fails in production and introduces the fundamentals of live documentation, actionable goals, and validation gates. With real-world examples and tools like GitHub Spec Kit and Model Context Protocol (MCP), this course helps software managers and architects natively and standards-align AI-powered code and modernize legacy systems without inheriting technical debt.
What you will learn
- Design a complete workflow from specification to plan, then tasks, and finally implementation for AI-assisted software engineering.
- Write machine-interpretable specifications using EARS syntax and remove ambiguities using disambiguation gates.
- Create a project constitution and agent instruction files to manage AI behavior with defined boundaries.
- Safely organize and direct multiple specialized and sub-agent AI agents while maintaining the integrity of the system architecture.
- Master the full SDD process cycle including defining measurable success metrics without mixing up implementation details.
- Implementing mandatory verification gates before code merging and using feature-based tests derived from EARS stability.
- Create a business case for SDD using real-world productivity data and design a step-by-step implementation plan for the organization.
This course is suitable for people who:
- Software engineers who want to move beyond prompt engineering and into structured development aided by AI.
- Technical leaders and software architects who are responsible for the design, maintenance, and sustainability of production-stage systems.
- Engineering managers who are evaluating how to safely scale AI across diverse teams and complex codebases.
- Senior system designers looking to reduce AI indeterministic behavior and control costs in software projects.
Course Description: Spec-Driven Development: designing deterministic AI systems
- Publisher: Udemy
- Instructor: Skliar Serhii
- Training level: Beginner to advanced
- Training duration: 8 hours and 54 minutes
- Number of lessons: 33
Course topics
Prerequisites for the Spec-Driven Development: designing deterministic AI systems course
- Basic understanding of software development concepts such as APIs, testing, and version control
- Familiarity with AI coding tools like ChatGPT, Claude, Copilot, or Cursor is helpful but not required
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 1080p
Download link
Rapidgator link
File(s) password: www.downloadly.ir
File size
12.4 GB
