Senior AI System Engineer

Lech Kalinowski

Lech Kalinowski

Lech Kalinowski is a data scientist and machine learning expert with a PhD in Physical Sciences. His background spans physics, AI, blockchain, and cybersecurity, with experience turning advanced research into practical products and business value across startups and enterprise environments.

Lech Kalinowski is a data scientist and machine learning expert with a PhD in Physical Sciences.

His background spans physics, AI, blockchain, and cybersecurity, with experience turning advanced research into practical products and business value across startups and enterprise environments.

What I’ve been shipping

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Talk
11/4/2026

Quantization Impact on LLM Quality: A Case Study of Apex

Artur Morys-Magiera and Lech Kalinowski share findings from 344 benchmark runs with Apex, our Gemma-based LLM, examining the trade-offs between model size, decode speed, and quality.
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Talk
9/15/2026

No Framework, No Server: Making AI Agents Collaborate in One Terminal

Lech Kalinowski will show how Agents Commander lets multiple AI coding agents collaborate directly in one terminal without a central server or heavyweight framework.
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Live Stream
8/27/2026

Graph Agentic Coding Extends AI Workflows

How connected state, retrieval, memory, and verification carry coding agents across complex, multi-step workflows. Kewin Wereszczyński and Lech Kalinowski discuss the structures that let agents plan, retrieve context, use tools, and keep working across longer tasks.
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Article
8/21/2026

Automating React Native Evals With Airflow

How Airflow coordinates React Native Evals, runs solver and judge models separately, and keeps every result traceable through human review.
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Article
7/22/2026

Building Vault: A Dual-Screen Terminal for Self-Hosted AI Agents

See how Vault uses an ESP32, OLED, and e-paper display to control an OpenClaw agent and a locally served LLM on a DGX Spark.
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Article
5/21/2026

Agencies or Swarms? What Small Model Cooperation Means for AI Engineering

A hands-on look at agentic swarms, distributed inference, and what small-model benchmarks suggest about future AI infrastructure.
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Live Stream
5/7/2026

Improve Your AI Coding Workflow With Cursor Tips and Tricks

Explore practical tips for working with AI coding agents, managing context, using skills, reviewing code, and choosing the right models.
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Article
4/27/2026

When to Use Apple Foundation Models on Mobile

Apple’s Foundation Models framework gives mobile teams a practical local-first option for short, privacy-sensitive, and low-latency tasks, while cloud models still handle the heavier work.
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Talk
4/20/2026

Ambient Generative AI: Deploying Latent Diffusion Models on Mobile NPUs

Join Lech Kalinowski at AI Engineer Miami on April 20–21 for a talk on running offline latent diffusion models on mobile NPUs.
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Article
4/1/2026

Agents Commander: A Lightweight Interface for Multi-Agent CLI Workflows

Manage and connect multiple AI agents in a CLI with a simple communication protocol.
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Article
3/27/2026

RAG Is Dead. Long Live Context Engineering for LLM Systems

When should you skip RAG? Learn how structured context and direct LLM APIs can replace retrieval pipelines in many systems.
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Article
3/18/2026

A Practical Guide to LLM Model Naming Conventions

Learn how to read LLM naming conventions and choose the right model for your hardware. Discover what Q4, INT8, GPTQ, and GGUF mean and why models appear in multiple variants.
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Live Stream
3/12/2026

React Native Evals: Measuring AI Code Quality in Practice

React Native Evals introduces a data-driven way to measure how AI coding models perform on real React Native development tasks.
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Article
3/5/2026

Announcing React Native Evals

We built an open-source benchmark to measure how AI coding models handle real React Native tasks, such as animations, async state, navigation, and more.

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