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Home Insights Ebooks Vibe prototyping: Where AI in SDLC delivers outcomes

Despite the rapid adoption of AI in the SDLC through copilot-style tools and LLM-native IDEs, why do business outcomes continue to lag behind productivity gains?

Only about 8% of the idea-to-production timeline is spent coding. AI-assisted coding improves velocity, throughput, and code volume, but it does not materially reduce time-to-value. As a result, 40–50% of innovation initiatives fail to meet revenue expectations, despite clear gains in developer productivity.

Leading organizations are responding by shifting focus to ideation through vibe prototyping.

Download the ebook to learn how vibe prototyping helps teams validate ideas earlier, reduce uncertainty sooner, and invest only in initiatives with real business potential.

Three key principles of vibe prototyping

Use these three principles to redesign how your teams test ideas, validate value, and move only the strongest opportunities into delivery.

 

Compress the R&D timeline into a 48-hour sprint

Vibe prototyping compresses the traditionally slow R&D timeline into a focused 48-hour innovation sprint.

  • Day 1 is dedicated to defining hypotheses, success criteria, and validation scenarios.
  • Day 2 is focused on delivering a working prototype and validating it with users.
Clock face emerging from colourful fluid
 

Optimize for evidence, not artifacts

The outcome is user-validated prototypes that support faster prioritization, clearer funding decisions, testing of new revenue streams, and stronger alignment across stakeholders. Instead of celebrating code volume or polished demos, vibe prototyping emphasizes instant feedback loops (change, run, observe in seconds), live UX experiments across flows and edge cases, and “wow” moments delivered during real user sessions.

Silhouette of a person working on a laptop
 

Govern AI-augmented development with a spec-driven approach

Vibe prototyping is not about generating UI faster. Rapid agentic AI coding is easy to mistake for progress, but speed alone doesn’t create value. Differentiation comes from how ideas are validated and governed. At Grid Dynamics, vibe prototyping is a formal product development phase designed to replace traditional proof-of-concept efforts through a spec-driven Research–Plan–Act (RPA) approach that aligns naturally with modern, agentic AI delivery models.

Steps ascending a vibrant landscape

How vibe prototyping transforms software delivery

Cubes forming a digital city on screen

Turn proofs of concept into executable evidence

Instead of disposable demos, vibe prototyping produces a backlog of verified, prioritized ideas that can move directly into implementation. Hypotheses are defined before generation, and every prototype is grounded in real architectural and technical constraints.

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Hourglass surrounded by vibrant, colourful waves

Make 48 hours the new innovation standard

Teams move from idea to user-validated prototype in just two days. This compresses months of design and prioritization into a tight, repeatable sprint that reduces uncertainty early and accelerates time-to-value.

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Profile of a person with flowing, colourful waves

Align strategy, product, and engineering around real users

User-validated prototypes create a shared view of what “good” looks like. Instant feedback loops, live UX experiments, and real user sessions give stakeholders concrete evidence to prioritize, fund, or pivot initiatives.

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Person in profile working on a glowing laptop

Put governance at the center of AI-rapid prototyping

Through the Research–Plan–Act (RPA) approach, hypotheses are defined first, research grounds ideas in reality, planning turns insights into execution-ready intent, and AI agents execute under clear constraints with human review at every critical transition.

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Geometric blocks in a digital landscape

Scale across industries with proven patterns

Through real-world examples in retail, manufacturing, and food distribution, the ebook shows how vibe prototyping turns speculative PoCs into executable evidence, compressing months of design and prioritization down to days as the software value stream evolves from code completion to AI-native, agentic delivery.

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Contributing authors

Pavel Azaletskiy

Pavel Azaletskiy

Head of Cloud & DevOps Practice

Pavel Azaletskiy is a computer scientist, former AI researcher, and business leader with 20+ years in software. As Head of Cloud & DevOps at Grid Dynamics, he drives AI-powered cloud and DevOps strategy, focusing on AIOps, AI SDLC, developer productivity, and operational excellence.

Vladimir Kondraschenko

Vladimir Kondraschenko

Principal Solutions Architect

Vladimir Kondraschenko is a Principal Solutions Architect at Grid Dynamics, leading modern application development and advising enterprises on architecture and AI-driven solutions. He specializes in Java, distributed systems, and cloud-native tech, with a PhD in Computer Science and extensive publications.

Nikita Ivanov

Nikita Ivanov

VP of Technology, AI

Nikita is a technology executive and product-driven innovator with 25+ years of global leadership in AI and software engineering. He has led GenAI and data platforms, advises executives on AI strategy, is a Forbes Technology Council member, startup mentor, investor, and a recognized expert in distributed systems.

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