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Serhii Yakovenko

Serhii Yakovenko

Engineering leader with 10+ years of experience in software development, QA, and team leadership. Passionate about delivering high-quality products, empowering teams, and fostering a culture of collaboration and continuous growth. Skilled in engineering management, project execution, and aligning technical excellence with business goals.
Engineering Leader, UKyakovenkoserhii
AI-Powered Code Review
TechLead Conf Amsterdam 2026: Adopting AI in Orgs EditionTechLead Conf Amsterdam 2026: Adopting AI in Orgs Edition
Jun 2, 14:00
AI-Powered Code Review
Workshop
Every engineering organisation is experimenting with AI coding assistants, but few have built production-grade LLM integrations into their core developer infrastructure. I have such an experience, and I will share real patterns from deploying an AI-powered code review system across a 400+ person engineering organisation (~200 developers) — covering a competitive evaluation of 4 tools across 18 dimensions, building a webhook-based review architecture with slash commands and auto-review, evolving context enrichment from static rules to AI-powered document selection, managing a 4-model fallback chain on Vertex AI, and measuring impact through a feedback dashboard. Attendees will leave with a battle-tested
playbook for integrating LLMs into their own engineering workflows — not as toys but as production infrastructure.

Workshop Structure
1. The Code Review Bottleneck at Scale
2. Tool Evaluation — 4 Candidates, 18 Dimensions
3. Architecture — Webhook Server & Auto-Review
4. Context Enrichment — From Path Rules to AI- Document Selection
5. Model Strategy — Migration & Fallback Chain
6. Measuring Impact — Feedback Dashboard
Register
code quality
Halving Your CI Pipeline – Practical Optimisation Strategies
JSNation 2026JSNation 2026
Upcoming
Halving Your CI Pipeline – Practical Optimisation Strategies
Every minute added to your CI pipeline costs real money and real developer time. At ~45 MRs per day and ~340 pipeline runs, a single minute of pipeline overhead translates to nearly 6 hours of lost engineering time daily. This talk presents the complete playbook we used to reduce our Merge Train pipeline from about an hour to about 22 minutes — a ~64% reduction — while improving CI health from the low 80s to the low 90s percent. Covering compute instance migration (with real benchmark data from 10 runs per configuration), service test extraction, CloudWatch optimisation, linter caching, flaky test detection, and cost analysis, attendees leave with a prioritised framework for their own CI optimisation efforts. Every optimisation includes before-and-after metrics, cost impact, and the trade-offs we navigated.
devops
Halving Your CI Pipeline – Practical Optimisation Strategies
Web Engineering Summit 2026Web Engineering Summit 2026
Upcoming
Halving Your CI Pipeline – Practical Optimisation Strategies
Every minute added to your CI pipeline costs real money and real developer time. At ~45 MRs per day and ~340 pipeline runs, a single minute of pipeline overhead translates to nearly 6 hours of lost engineering time daily. This talk presents the complete playbook we used to reduce our Merge Train pipeline from about an hour to about 22 minutes — a ~64% reduction — while improving CI health from the low 80s to the low 90s percent. Covering compute instance migration (with real benchmark data from 10 runs per configuration), service test extraction, CloudWatch optimisation, linter caching, flaky test detection, and cost analysis, attendees leave with a prioritised framework for their own CI optimisation efforts. Every optimisation includes before-and-after metrics, cost impact, and the trade-offs we navigated.
devops