Скачать или смотреть Python AI Agents with Pydantic AI: Example & Interview with Pydantic Creator

Dive deep into the future of building with LLMs in this comprehensive look at the Pydantic AI agent framework. If you're a Python developer navigating the chaotic world of AI agent frameworks, this video will show you a more reliable, developer-friendly path forward.

We move beyond theory to build a practical, production-ready flight booking AI agent from scratch. You'll learn how Pydantic AI's python-centric design makes development more intuitive and how its seamless integration with Logfire provides the critical observability needed for real-world applications.

The highlight of this video is an exclusive, in-depth interview with Samuel Colvin, the creator of Pydantic. We ask him the tough questions about why he built a new agent framework, how Pydantic AI plans to compete with established players, his philosophy on open-source business models, and his vision for the future of Python.

0:00 - Intro
2:07 - Introducing Pydantic AI: The "FastAPI Feeling" for AI
4:00 - Installing and using Pydantic AI and Logfire in a Flight Booking Example
15:11 - Exclusive Interview with Pydantic Creator, Samuel Colvin
27:27 - Key Takeaways

Key Interview Topics with Samuel Colvin:
The "JavaScript framework wars" of AI agents.
What existing frameworks are doing wrong.
Pydantic AI's competitive moat as models get smarter.
The decision to build Logfire instead of using existing observability tools.
The future of Python and the Pydantic V2 rewrite in Rust.
The tension between open-source community and commercial products.

Resources:
GitHub Repo with Full Code Example: https://github.com/pydantic/pydantic-...

#Pydantic #Python #AIAgent #LLM #Developer #ArtificialIntelligence

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