Illia Pantsyr | Blog

How a chat conversation actually reaches the model, and why it can still confuse untrusted content with trusted instructions.

Why conversational AI systems trade off between capability, control, and latency, and why the latency corner is effectively fixed.

Notes from a YOW!

Notes from Jim Donovan's talk on client service: drop the jargon, use pauses, and offer advice that runs counter to your own interest.

How Clio surfaces usage patterns across millions of Claude conversations while keeping any individual conversation private.

Notes on an Epoch AI report asking whether GPU failure rates and checkpointing overhead put a ceiling on how large training clusters can grow.

A summary of the paper showing that models retrieve far more reliably from the start and end of their context than from the middle.

All-at-once, in-place, blue/green, canary and shadow deployments: how each works, what it costs, and when the complexity pays off.

Taking a Spring Boot image from 465MB down to 184MB with multi-stage builds, jlink, jdeps and a leaner base image.

What changed in Datafaker 2.0: schemas and transformers, Java Records support, and generating large volumes of test data.

How the JVM finds, loads and links a class, and what each of the bootstrap, platform and application class loaders is actually responsible for.