Technically Monthly (November 2025)

How machines learn from data, what happens after you vibe code an app, and how to build AI products that don't embarrass you in production.

Nov 5 • 

Justin

 and 

David

12

October 2025

How to build AI products that are actually good

All about AI evals, plus how Braintrust helps companies build better AI apps.

Oct 23 • 

Justin

25

The vibe coder’s guide to real coding

Things you should know as a vibe coder that will make your app actually work / not die.

Oct 22 • 

Justin

39

How Vercel became the f̶r̶o̶n̶t̶e̶n̶d̶ AI cloud

And why building AI products requires new forms of infrastructure for developers.

Oct 21 • 

Justin

21

What is Machine Learning?

How computers learn patterns from data: the foundation for everything from stock price prediction to ChatGPT.

Oct 7 • 

Justin

30

Technically Monthly (October 2025)

Why AI models hallucinate, why building MCP servers is hard, and the scaling law driving trillion-dollar AI bets.

Oct 1 • 

Justin

 and 

David

21

September 2025

The scaling law and the “bitter lesson” of AI

AI experts all HATE this one law!!!

Sep 23 • 

Nicole Errera

27

1

A deep dive into MCP and its associated servers

A brief history of the protocol, why it can be hard to use, and how FastMCP came to be.

Sep 16 • 

Justin

48

Why do models hallucinate?

AI models inherently make stuff up. What can we do about it?

Sep 9 • 

Nicole Errera

40

Technically Monthly (September 2025)

A beginner’s guide to AI model architectures, why open source licenses aren’t as simple as “free to use,” the evolving role of product documentation…

Sep 2 • 

Justin

 and 

David

23

August 2025

Databricks is apparently worth $100B. What do they even do?

Or perhaps more accurately: what does Databricks NOT do?

Aug 25 • 

Justin

40

What's documentation?

Why sometimes, you need to tell people how to do things

Aug 19 • 

Justin

36

1