// profile
About
Yuriy Daybov
Chief Technology Officer · CTO
VP of Engineering
20+ years building software products and platforms, 5+ as CTO. I specialize in software engineering turnarounds and technology transformation at product-focused companies: rebuilding teams, rearchitecting systems, establishing development processes from scratch.
I understand the architecture and limitations of modern AI systems (LLMs, agentic approaches) — and know how to prepare the technical and organizational environment for their practical application.
Author of a Telegram channel on artificial intelligence, covering the architecture, limitations, and practical use of modern AI systems.
// expertise
How speed and efficiency are achieved
SDLC Design for Product Pace
Building a development cycle that doesn't slow down product hypotheses: CI/CD, release cadence, testing strategy.
Setting up CI/CD pipelines, release cadence, and testing strategy aligned with real product needs.
Goal: shorten the path from idea to production while keeping releases stable and predictable.
Measurable targets: deployment frequency, commit-to-production time, release stability.
Teams Built for Delivery
Team structure, roles, and processes that minimize time-to-market.
Developing tech leads who make decisions autonomously without creating bottlenecks.
Balancing speed and reproducibility: a process that works without manual steering.
Team topology that enables independent releases and clear ownership.
Architecture for Speed of Change
Technical decisions that don't become a drag six months later: service boundaries, contracts, tech debt management.
Service boundaries that let teams release independently.
Managing tech debt as an investment process, not a fire drill.
Contracts between components that reduce the cost of change.
AI in the Engineering Cycle
Practical integration of AI tools into development: code review, generation, testing — with attention to risks and limitations.
Integrating AI-assisted tools into the development workflow: code review, generation, testing.
Preparing the technical and organizational environment for AI-assisted development.
Risk and limitation assessment — not everything that can be automated should be.
// stack
Technology Background
Languages
Backend
Frontend
Data
Messaging
Infrastructure
Observability
Mobile & IoT
Practices & Tools
Contact
Let's talk
Open to advisory, fractional CTO, and strategic technology consulting engagements.
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