Spec-Driven Development: From Vibe-Coding to AI Engineering
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Unclaimed ProfileIn the rapidly evolving landscape of AI-assisted software engineering, many developers fall into the common trap of 'vibe-coding'—relying entirely on raw, unstructured prompts and hoping that large language models will output stable, functional code. This course, 'Spec-Driven Development: From Vibe-Coding to AI Engineering' created by Skliar Serhii, offers a rigorous, highly structured antidote to this unpredictable approach. Designed for software developers, technical product managers, and systems architects, the curriculum guides you through establishing a repeatable, professional Spec-Driven Development (SDD) workflow. Students will learn to construct machine-interpretable requirements using the structured EARS framework, formulate precise project constitutions, and implement three-tier boundaries for autonomous AI agents. By utilizing human-in-the-loop verification gates and test-driven specifications, you can steer complex AI processes with absolute predictability. This shift from ad-hoc prompt engineering to deterministic spec engineering ensures that your codebase remains clean, reliable, and immune to drift, turning modern generative AI tools into dependable, scalable engineering assets.
About the creator
Skliar Serhii
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Skliar Serhii is a seasoned software engineer and technical educator dedicated to bridging the gap between rapid prototyping and production-grade artificial intelligence systems. With a strong foundation in modern software architecture, Skliar has witnessed firsthand the evolution of coding practices from speculative, ad-hoc "vibe-coding" to structured, spec-driven engineering methodologies. His teaching philosophy centers on systematic design, rigor, and the strategic integration of AI tools within the development lifecycle. Instead of relying on guesswork, Skliar advocates for precise specifications, robust testing frameworks, and clear architectural boundaries to build predictable, scalable AI applications. Through his course, "Spec-Driven Development: From Vibe-Coding to AI…Show more
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Program Overview
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Learning format
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Price may change · updated within 1–2 weeks
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What You'll Learn
- Build a repeatable Spec-driven development workflow (specify - plan - tasks - implement) to ship AI-assisted features without “house of cards” code
- Write machine-interpretable requirements using EARS, clear acceptance criteria, and explicit constraints to prevent agent guesswork and drift
- Set up project governance for AI agents with a constitution, agent instruction files, and three-tier boundaries (always do, ask first, never do)
- Convert specs into atomic, reviewable task lists and run human-in-the-loop verification gates to keep implementation aligned with intent
- Apply test-driven specs, verification gates, and property-based testing to prove critical behavior and detect drift early
Best For
- Software engineers looking to transition from reactive prompt engineering to structured, reliable AI-assisted workflows.
- Technical leads and engineering managers who need to maintain code quality while scaling development with LLMs.
- Developers tired of 'vibe-coding' who want to implement repeatable, deterministic development processes.
- Systems architects aiming to integrate human-in-the-loop governance for autonomous AI agent tasks.
Not For
- Absolute beginners who are currently learning the basics of programming syntax or standard software development life cycles.
- Developers who are strictly interested in casual, ad-hoc generative AI prompting without formal engineering constraints.
- Professionals seeking a general overview of AI trends rather than a deep, technical methodology for production code.
- Non-technical stakeholders who do not have the capacity to apply structural frameworks or manage AI agents directly.
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