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unitcraft/README.md

🇷🇺 Русский | 🇬🇧 English

👋 Hi, I'm Evgeny Golovin

Engineering Manager · Author of Nova Lang · Banking & Fintech · Remote across Russia

Started as a developer — 3D mobile games in C++, web services in Java, Go, C#, TypeScript, PHP, React, full stack. Moved into management and have been leading IT product development for 10+ years — from idea to production. Currently working in banking, heading distributed teams remotely, designing my own programming language Nova and using AI agents as part of everyday work.

10+ years 5+ years 5+ years
engineering management web development · Java · Go · C# · TS · PHP · React 3D mobile games · C++

🚀 Nova — a programming language for the AI era

«LLM writes the code — human reviews it». The first language designed for this era.

Algebraic effects make side effects visible right in the function signature. Reading a single line, a reviewer knows whether the function hits the DB, the network, reads the clock, or can fail — without reading the body. This changes the game for reviewing AI-generated code.

fn process_order(o Order) Db Net Time Fail -> Receipt

The signature alone says: the function uses the database, makes network requests, reads the clock, and can fail — and nothing else.

What makes Nova special

  • Effects + handlers — tests without mocks, the exact same code in production and tests
  • 🔀 No async/await — structured concurrency, no «function colour»
  • 🛡️ Contracts from Go to F* — a gradient from script to verified code in one language
  • 🎯 Capability securityforbid Net, Fs blocks an effect at compile time
  • ⏱️ Realtime blocks — the compiler guarantees no GC pauses for audio/trading/embedded
  • 🔄 Time-travel debugging — a natural consequence of handlers

🔗 GitHub · GitVerse

🤝 Grow Nova together

Looking for partner companies for contribution, sponsorship and joint research. Happy to discuss any format of collaboration — from one-off patches to a dedicated team.

💼 Hiring

Open to engineering leader roles — especially with teams where AI tools and modern engineering practices are already part of the culture.

✉️ unitcraft@inbox.ru


🤖 AI agents in practice

✍️ Writing code

  • Scaffolding new services from scratch
  • Refactoring legacy code without breaking business logic
  • AI code review: SOLID violations, vulnerabilities, code smells
  • Tools: Claude Code, Cursor, GitHub Copilot

🧪 Testing

  • Generating unit and integration tests directly from code
  • Building test cases and checklists from requirements and user stories
  • Edge-case and boundary condition discovery
  • Generating test data, mocks and stubs

🏗️ Architecture

  • Designing microservice solutions with explicit trade-off analysis
  • AI as a second voice in architecture sessions
  • Writing Architecture Decision Records (ADR) with the agent
  • Load analysis, bottleneck and failure point detection

📐 System analysis

  • Breaking down business requirements into technical tasks
  • API contracts, integration diagrams and data flows
  • Generating documentation: README, runbooks, API descriptions
  • Risk analysis and system degradation scenario planning

💡 IT solution design

  • Analysing existing systems and making improvement recommendations
  • Comparing tech stacks with banking and CII compliance in mind
  • Preparing technical presentations for stakeholders
  • Forming vendor and off-the-shelf solution evaluation criteria

🛠️ Stack

AI agents: Claude Code · Cursor · GitHub Copilot Languages: Java · Go · C# · TypeScript · PHP · C++ · Rust · SQL Frontend: React · TypeScript Databases: PostgreSQL · MSSQL · MySQL · Oracle · Kafka Frameworks: Spring Boot · Spring Cloud · Hibernate DevOps: Docker · Kubernetes · OpenShift · GitLab CI · Jenkins Processes: Scrum · Agile · Code Review · CI/CD · SDLC


🏆 Results

Metric Before After
Release cadence 3 per year 4 per quarter
Contact centre load baseline −20%
Time-to-Market baseline −20%
Critical bugs in prod recurring 0

📧 unitcraft@inbox.ru

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