Vadym Soroka

Scaling AI-assisted development in enterprise: from code generation to engineering discipline

By 2027, successful AI adoption in development will depend not on code generation speed, but on integrating AI tools into controlled testing, security, and architectural oversight processes.

Integrating AI/ML into products: From prototype to production

Transitioning from experimental ML models to robust enterprise systems using AWS Well-Architected Framework, Google SRE, and 12-Factor App principles.

Platform engineering and IDP: accelerating development teams

Implementing platform engineering and an Internal Developer Platform (IDP) transforms infrastructure into a product, reducing operational complexity and improving key DORA metrics.

From MVP to production-ready: architectural discipline

Transforming a successful prototype into a stable enterprise solution using the 12-Factor App, SRE practices, and the Well-Architected Framework.

Architectural defense against AI Prompt Injection and leaks

How to protect corporate LLM systems from Prompt Injection and data leaks at the architectural level in 2025, following NIST AI RMF and OWASP standards.

Enterprise developer: from code to AI system management

AI-native development is transforming the role of the enterprise developer in 2026-2027, shifting focus from writing code to managing AI systems, security, and domain-specific models.

Domain-specific models: when corporate AI needs its own language

Corporate systems require domain-specific language models for security, efficiency, and compliance with unique business processes.

AI voicebots in telecom: balancing efficiency and customer trust

AI voicebots in telecom contact centers enhance efficiency but require a balance between automation and customer trust.

AI Assistants for Contact Centers: From Chatbots to Voice AI

Domain-specific AI models for enterprise applications

Domain-specific AI models are becoming a key tool for modernizing enterprise applications in 2026-2027, overcoming legacy system limitations.

AI Act compliance for AI communications in telecom

Telecom operators must proactively prepare data and enhance cybersecurity to comply with the EU's AI Act, minimizing fraud risks.

AI Act and the future of communications: challenges for VoIP and contact centers

The AI Act is changing the game for telecom operators. How to prepare VoIP and contact center data and architecture for new regulatory requirements and current challenges.