The five levels of the certification.

Ability to use generative artificial intelligence to produce simple elements from guided instructions: interface generation, component edits, page creation or basic automations in a supervised environment. The candidate understands the fundamentals of vibe coding — prompting, iteration, minimal product logic and collaboration with a generative AI on a narrow scope. Output remains experimental, hard to maintain, and requires substantial support to be finalised or deployed.

Recommended for students, career changers, teams discovering generative-AI-assisted development, and anyone wanting to build their first prototypes without a solid technical background.

Ability to turn a simple business need into a coherent interactive prototype: structuring a user journey, building essential features, improving iteratively with generative AI and connecting to basic external services. The candidate begins to reason in terms of product rather than mere screen generation. They can debug with AI assistance, structure their work and ship a first usable experience on a limited scope. The resulting applications remain suited to internal use, demos or early MVPs.

Recommended for junior product builders, designers, operations managers, marketers, entrepreneurs and innovation teams looking to prototype quickly without immediately depending on an engineering team.

Ability to independently design and ship a working web application generated and iterated with generative AI: simple architecture, data management, authentication, API integration and deployment to real environments. The candidate can maintain an existing codebase, improve performance, fix complex errors and evolve a product as usage grows. Practices become structured: versioning, component logic, code organisation, baseline quality, dependency management and collaboration with modern AI-augmented tooling.

Recommended for product owners, technical project managers, hybrid designers, entrepreneurs, innovation consultants and anyone able to carry an MVP or internal tool on their own.

Ability to ship to production an application intended for real users, to professional standards: reasoned architecture, security, observability, performance, access management, critical integrations and operational reliability. The candidate has mastered modern AI-augmented workflows — code review, testing, advanced debugging, CI/CD, Git collaboration, maintaining a complex codebase and continuously evolving a digital product. They can arbitrate between speed of generation and technical robustness, document their decisions and maintain a product over time.

Recommended for founders, intrapreneurs, innovation engineers, technical lead designers, technical product managers and autonomous builders responsible for a product running in production.

Ability to design, orchestrate and evolve complex generative-AI-driven digital systems in critical or large-scale environments. The candidate moves beyond application building to steering a genuine production architecture: AI agents, multi-service workflows, tool orchestration, advanced integrations, distributed systems, monitoring, cost optimisation, advanced security and technical governance. They can structure robust and scalable architectures, take over complex existing systems, design reliable autonomous workflows, industrialise AI usage, define technical standards, lead hybrid human + AI teams and arbitrate long-term technical, product and infrastructure decisions.

Recommended for AI-augmented CTOs, AI product architects, technical founders, advanced automation experts, AI transformation leads and builders steering complex digital systems at scale.