AI is leverage, not ownership transfer.
The tool can draft, suggest and accelerate. The engineer still owns the decision, the tradeoff and the consequence.
A practical journal on building production-ready software in the AI era.
From messy ideas to production-grade systems.
Igor Sinitsyn writes about the practical side of AI-assisted development: how to explore ideas faster, shape reliable architecture, organize delivery and turn engineering chaos into an operating rhythm.
For developers, tech leads, CTOs, founders and AI-curious operators who care about shipping real software.
Written by
Igor Sinitsyn
CTO / Tech Lead with 20+ years in production web development, team building and business-minded engineering.
Explore with AI
Use prompts, agents and vibe coding to move from uncertainty to prototype without losing product context.
Engineer the path
Clarify requirements, architecture, ownership, tests and review before the demo becomes technical debt.
Ship and operate
Deploy, monitor, measure and improve the system so it keeps working after launch.
20+years dev
CTOoperator lens
AIwith discipline
AI-assisted development
Vibe coding
Production architecture
Engineering operations
Team systems
Why this exists
A personal field journal for serious builders in the AI era.
From Vibe to Production is not a course, funnel or guru brand. It is a public notebook about what happens when modern AI tools meet real delivery pressure, legacy systems, teams, deadlines and users.
Igor shares lessons from the build: the experiments that work, the shortcuts that become expensive, the prompts that help, the architecture that survives and the operating habits that turn momentum into repeatable delivery.
What Igor believes
Fast is only impressive when the system keeps working.
AI changes the speed of exploration. Production still rewards clarity, ownership, feedback loops and respect for business reality.
User value and business value must meet.
A good system helps real people and makes operational sense for the company paying to maintain it.
Chaos becomes progress only through process.
Requirements, review, tests, metrics and rituals are not bureaucracy. They are how teams keep speed from turning into fire.
The best teams make reality visible early.
Transparent communication, constructive conflict and short feedback loops beat perfect plans hidden inside task trackers.
What Igor writes about
Vibe coding, but with production consequences.
Posts are built around real engineering experience: how to prototype faster, keep quality visible, reduce chaos and turn decisions into business value.
AI-assisted development
How to use AI tools as leverage without outsourcing judgement, ownership or engineering standards.
Vibe coding to production
What happens after the exciting demo: contracts, tests, review, rollout and maintainability.
Production architecture
Pragmatic boundaries, explicit flows and systems that future teams can understand and change.
DevOps & operations
Deploys, logs, metrics, alerts, incidents and the boring habits that protect users from chaos.
Engineering management
Hiring, mentoring, 1:1s, retrospectives, planning, feedback and healthy team operating systems.
Automation workflows
Where agents help, where they break and how to design human-reviewable outputs.
Product delivery
How to move from idea to feature to workflow while balancing users, business value and cost.
Code quality & testing
Tests, acceptance criteria, code review and quality gates as a way to ship faster with less drama.
Developer workflows
Practical systems for prompts, tools, docs, task decomposition and smoother daily execution.
Impact-first background
Not theory. Production scars, team building and shipped systems.
Igor writes as someone who has coded, led teams, hired developers, improved delivery flow and worked across e-commerce, edtech, travel and fintech environments.
20+years in web development
50+technical interviews conducted
70%time-to-market reduction in a team transformation case
C1English for global engineering conversations
Fintech, fiat & crypto · high-trust product delivery
Building in an NDA fintech context where delivery decisions affect money movement, reliability, trust and operational control — exactly the kind of environment where AI speed must be balanced with architecture and risk awareness.
Bnberry · built the team and delivery rhythm
Built and managed a distributed 5-person development team from scratch, owned feature requirements, code review, delivery flow and growth plans, helping developers become stronger while keeping product work moving.
EdTech · 70% faster time to market
Led two teams of 10+ developers and made delivery more predictable by introducing agile practices, technical design review and acceptance tests — reducing time to market by more than 70% and lowering QA dependency.
Lamoda · business-critical internal tools
Worked on internal systems with Symfony, Vue, MySQL/PostgreSQL and Docker, focusing on architecture, tests, bug fixing, code review and process improvements that reduce friction between business and engineering.
Westwing · operational backbone for e-commerce
Built and evolved back office, CRM, supplier portal, CMS, reporting and mailing platforms using PHP, React, RabbitMQ, Redis, Docker and AWS, while helping extract microservices from monoliths and raising quality through review, tests and documentation.
How Igor works
From unclear request to operating flow.
The recurring pattern: understand the business, shape the product path, make the engineering work explicit and create a process that keeps improving after release.
01Start with the business pain.
What hurts, who feels it, and what must become easier after the feature ships?
02Translate chaos into decisions.
Requirements, tradeoffs, estimates, risks and ownership become visible before implementation.
03Build with feedback loops.
Code review, tests, acceptance criteria and demos keep the system aligned with reality.
04Operate what was shipped.
Metrics, alerts, logs and support flow help find the problem before users do.
Follow the build notes
Follow Igor if you want AI to help you build better systems, not just faster demos.
The experiments, tradeoffs, failures, workflows and practical wins are published on LinkedIn. Connect if you care about AI-assisted development, engineering leadership and software that survives real users.