
Get insights into using AI for real world scenarios.
| Platform | Pricing | Only free issues | Publishes | Daily | |
|---|---|---|---|---|---|
| Issues | 33 | Founded | 2 years ago | Last Issue | 12 days ago |
| Active | |||||

Recap: part 1 was validation basics, part 2 was fields and constraints, part 3 was nested models, part 4 was config. In production, you don’t call .model_validate() by hand — a framework does it on every request. Usually, that’s FastAPI....
AI agents change the security problem.
A chatbot can give you a bad answer.
An agent can send the email, access the account, visit the website, download the file, or spend the money.
That makes a simple question much harder:
What happ...
A missing environment variable took down a production deploy at 3am. Not a bad request. Not bad user input. The app’s own configuration was wrong, and nothing caught it until the app was already live. Here’s how Pydantic stops that.
Quick...
Quick recap before we start: Part 2 was about making one object strict: every field, the right type, the right length, the right pattern.
But here’s the thing: real data is never just one flat object. Think about it, an order has a custom...
In part 1, a missing email crashed our support bot three functions downstream. We fixed it with a type hint. Then someone submitted an empty name, a fake order ID, and a message longer than our database column — and every field passed.
A t...
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The writers behind this newsletter.
AI Engineering
I've built products for over a billion users at YouTube and Google Search. Now, I deconstruct complex systems and production AI for 80,000+ engineers each week. Subscribe to learn the principles behind building at hyperscale.
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