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VIBE CODING VS SPEC-DRIVEN DEVELOPMENT

August 4, 2026
Azade Foutouhi

Generative AI is changing the way software is created. Recently, two main approaches have appeared in AI-assisted development: vibe coding and spec-driven development (SDD). These approaches are not only techniques, but different ways of working with AI.

1. Vibe Coding

 Vibe coding is a term coined in 2025 to describe an approach to building software where requirements are expressed in natural language and AI generates the code.The process is very direct:

  • You give instructions
  • The AI generates code
  • You test and adapt it
  • You repeat the process

In this approach, the developer defines the goal, while the AI handles the implementation details.

This method is useful because it is easy to start and very fast. It allows people to quickly create prototypes, even without strong programming skills. It is often used for testing ideas, demos, or learning.

However, there are some  limitations. Since everything is driven by prompts, it can be hard to keep consistency. Over time, the code may become difficult to maintain or poorly structured.

2. Spec-Driven Development

Spec-driven development follows a different approach. Instead of generating code first, it starts by clearly defining what needs to be built.

Teams write specifications that describe:

  • Requirements
  • Constraints
  • Expected behavior

Then the development process follows structured steps: Define, Plan, Build, and Check.

In this model, the specification becomes the main reference for both humans and AI.

This approach helps to reduce misunderstandings and improve code quality. It is more adapted for large projects or when several teams work together, because it gives a clear shared direction.

3. Conclusion

Vibe coding and spec-driven development are not in competition. They are complementary approaches that go together and answer the same shift: AI becoming a co-developer.

Vibe coding focuses on speed and experimentation. Spec-driven development focuses on structure and long-term reliability.

In practice, combining both can help teams move fast while keeping good control over their systems.

References

About the author

ScientificLeader | France
PhD in autonomous navigation from UNSW; led AI‑based IoT behavior prediction and drone navigation projects at Capgemini. Now Scientific Leader at SogetiLabs, driving healthcare AI research, proposing solutions, monitoring progress, and building internal and external partnerships.

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