Leonid Igolnik
where else to find them
github:ligolnik
what they talk about
all 11 in the filters
where they keep going back
no series more than once — all 8 in the filters
on a stage with
all 4 in the filters
who talks about the same things
- Baruch Sadogursky110 talks
- John Willis31 talks
- Michael Nygard11 talks
- Jason Yee30 talks
- Andreas Grabner23 talks
- Michael Stahnke8 talks
| title | conference | date |
|---|---|---|
| Can We Trust AI-Generated Code? | AI By the Bay 2025 | 2025-11-17 |
Claims that LLMs produce correct code only about half the time (slide cites ~50% correctness and ~40% of AI code vulnerable) and that self-verification creates… | ||
| LLMs: Powering Lightning Fast Product Innovation | Great International Developer Summit 2023 | 2023-04-25 |
Clarify uses GPT APIs to turn call transcripts into smart summaries and action items, built end-to-end in about 15 days by chunking long transcripts, calling… | ||
| Devops@Scale | GeeCON 2019 | 2019-05-15 |
Starts at three engineers and scales to ~100, moving through clearly named stages: fire brigade, smoke alarm installers, then a centralized DevOps enablement… | ||
| #DataDrivenDevops | DevOps Conference Spring 2019 | 2019-03-25 |
Claims that cross-pillar metrics from dev QA and ops get integrated into actionable decisions with concrete results: measuring test‑environment utilization… | ||
| DevOps @ Scale — Greek Tragedy in Three Acts | DelEx Conf 2018 | 2018-02-17 |
A concrete scaling timeline for a DevOps team growing from 3 to 100 engineers, showing three stages: reactive firefighting, adding monitoring and processes… | ||
| Data-Driven DevOps | DelEx Conf 2018 | 2018-02-17 |
Presents a data-driven DevOps approach using three concrete metrics to start immediately: deployment frequency, pipeline lead time, and incident trend… | ||
| DevOps @Scale (Greek Tragedy in 3 Acts) | JavaDay Ukraine 2017 | 2017-11-04 |
Startup grows from 3 to ~26 to 100 engineers and the operations story follows: initial firefighting with Jenkins + AWS Beanstalk and a left-pad outage forces… | ||
| The Dark Arts of Performance Tuning | JavaDay Ukraine 2017 | 2017-11-04 |
A demo-driven walkthrough uses free JVM tools (jps, jinfo, jstack, JVisualVM with plugins, NetBeans profiler, Eclipse Memory Analyzer, GC logs) to find a… | ||
| Architecture Kata | JavaDay 2013 | 2013-10-19 |
Designs take raw GPS + Wi‑Fi scans from trucks, batch ftp upload at depot or stream from phones, store raw records in a sharded NoSQL store (Mongo), run a… | ||
| Patterns of SaaS: Refactoring Databases | JavaDay 2013 | 2013-10-19 |
Application runs across 6000 schemas with 76M transactions per week and performs half a million schema changes overnight by sequencing small, re-runnable… | ||
| The Dark Arts of Performance Tuning | JavaDay 2013 | 2013-10-19 |
Shows a concrete workflow that finds and fixes real bottlenecks using only free tools: measure CPU and kernel time with OS perf monitor, inspect threads and… | ||
| The dark art of performance tuning or how to become a performance hero ... | JDD 2012 | 2012-10-25 |
Shows how real Java apps at SaaS scale (4.8 million transactions in 90 minutes) get diagnosed and fixed using concrete tools and numbers: jvisualvm, jinfo… | ||
| nothing matches | ||