Applied AI, in practice.

Field lessons from production voice deployments: engineering natural conversations, testing integrations at scale, measuring conversion, and fixing the failures that only appear after real customers start calling.

• Human-sounding conversation design
• 1,000-call testing discipline
• Reliability and API failure management
• ROI and live deployment case studies

An invited lecture for Master of Science in Artificial Intelligence students on what happens after an AI demo works: choosing the right problem, designing around real constraints, and building systems through specifications and architecture.

A practical presentation on encoding the best salesperson's approach into production voice agents connected to live business systems. I also joined the event's expert panel to discuss deployment economics and applied AI.

• The "Cloner" deployment model
• AI-agent ROI framework
• Production voice architecture
• Expert panel discussion on applied AI

A Russian-language interview with the event host about AI capability, practical adoption, and the workflows that help teams move from curiosity to useful implementation in the trucking business.

A framework for prompt engineering as a professional competency: structuring context, choosing the right optimization method, and building repeatable workflows that produce consistent results.

A structured introduction to communicating with large language models, from prompt anatomy and iteration to retrieval, fine-tuning, reasoning techniques, and multi-agent creator-critic loops.