why every #AI engineer needs #Pydantic:

LLMs don’t return data. They return text that looks like data, most of the time. And “most of the time” is how production systems break.

I made a 6-minute video on why Pydantic is the one library every AI engineer should know:

→ One class does three jobs: it tells the model what to produce, validates what comes back, and powers autocomplete → Your function signature becomes the tool definition → Validation errors become feedback the model can fix itself → It’s already in your stack (OpenAI, Anthropic, LangChain, FastAPI…)

Plus a quick look at Pydantic AI, which runs that whole loop for you.

Prompts are suggestions. Schemas are contracts. 🎯

AI really changed how I work. I spent the last month learning how to use it to amplify my work, now I’m looking for projects where I can put that into practice at scale. Open for work!

A month learning to use AI to amplify your work before taking it to clients is the right sequence, Jacob. Putting it into practice at scale is where the real lessons show up. All the best finding the right projects.