ML Under the Hood

February 2026

Leaving the big enterprise, but keeping the enterprise AI lessons

What building secure AI agents taught me about architecture, evals, and why simplicity wins

Feb 8

10

October 2025

Schema-Guided Reasoning: What Changed in One Year

New learnings, industry adoption, and unexpected turns

Oct 8, 2025

7

September 2024

OpenAI o1 Benchmarks - and Streamlining Coding with o1-preview for Maximum Efficiency

Checking the performance of the new o1 models from OpenAI. Bonus: a practical tip on efficient coding with OpenAI o1-preview.

Sep 24, 2024

5

1

April 2024

New LLM Benchmarks, Enterprise AI Challenge

Hello, my Dear Reader.

Apr 7, 2024

5

February 2024

Enterprise LLM Platforms, AI Strategy and Continuous Learning

If we prove that this ChatGPT thing actually works, how can we quickly catch up with it? How can we employ this new flavour of AI across the company in…

Feb 12, 2024

3

November 2023

On ChatGPT-4, Mistral 7B OpenChat and OpenAI going vertical

Rate of the progress keeps up. Not all of it is locked behind OpenAI

Nov 12, 2023

8

October 2023

Underdog joins the fight

Underdog is the Mistral 7B model with unconventionally open source license. I'll also talk about AWS Bedrock, Anthropic, and Cloudflare Workers AI.

Oct 5, 2023

September 2023

On Chat GPT Dumbness, Trustbit Benchmarks and ML Product Labs

The reports of my dumbness are greatly exaggerated. (c) ChatGPT

Sep 10, 2023

August 2023

July 2023

Breaking the curse of LLM v2

New releases of large language models focus on efficiency. Sometimes quality is sacrificed. LLaMA v2 was a nice surprise.

Jul 18, 2023

June 2023

Open Source LLMs are Surprisingly Good

We can already replace GPT-4 with locally-run models in some products. Benchmarks help to pinpoint opportunities for migration. Results get only better…

Jun 25, 2023