Tag: pydantic-ai
17 posts
From create-react-app to create-ai-app: The New Default for AI Applications
In 2016, create-react-app standardized how we build frontends. In 2026, AI applications need the same moment — and it's here.
From 0 to Production AI Agent in 30 Minutes — Full-Stack Template with 5 AI Frameworks
Step-by-step walkthrough: web configurator, pick a preset, choose your AI framework, configure 75+ options, docker-compose up — working production AI app.
Same Chat App, 4 Frameworks: Pydantic AI vs LangChain vs LangGraph vs CrewAI (Code Comparison)
I built the same chat app 4 times with 4 different AI frameworks. Same FastAPI backend, same Next.js frontend, same PostgreSQL. Here's what the code actually looks like.
Build an AI PR Reviewer with 3 Parallel Subagents in Python
Security, style, and performance checks in 30 seconds — using pydantic-deepagents to run 3 specialized subagents in parallel against your git diff.
What I Learned at PyAI Conf in San Francisco — Where Python Meets Production AI Agents
Same-day recap from PyAI Conf — a 1-day conference hosted by Pydantic, FastMCP, and Theory Ventures, featuring Samuel Colvin, Sebastián Ramírez Montaño, Jeremiah Lowin, Armin Ronacher, and Guido van Rossum on the future of Python and production AI agents.
We Built a Web Configurator for AI Agent Apps — 75+ Options, Download as ZIP
246 template files, 5 AI frameworks, client-side rendering with Nunjucks — zero server, everything in your browser.
Sub-90ms Cloud Code Execution: How Daytona Replaced Docker in Our AI Agent Stack
Docker cold starts cost 2-5 seconds per sandbox. Daytona does it in under 90ms — here's how we integrated it into pydantic-ai-backend.
We're Building an Open-Source Claude Code Alternative in Python
Meet pydantic-deepagents — 5 modular packages, 30+ features, and a terminal UX that makes AI coding agents feel like a native dev tool.
Pydantic AI vs LangChain for Production AI Agents (2026)
A practical comparison of Pydantic AI and LangChain for building production AI agents. Type safety, streaming, dependency injection, and real-world trade-offs.
Hashline Edit Format: How 2-Character Hashes Fixed AI File Editing
How hashline edit format replaces error-prone str_replace with 2-character content hashes for reliable AI file editing. Benchmark results across 16 models and our Pydantic AI implementation.
Predictive AI: Give Your Agent a Docker Lab to Run Models
How to build an AI agent that runs sklearn predictions inside an isolated [Docker](https://docs.docker.com/) sandbox. Environment-as-a-tool pattern, sub-agent delegation, and structured chart output with Pydantic AI.
Why Your AI Agent Remembers Too Much (And How to Fix It)
Every memory system stores garbage. Here's how we solved it with file-based persistent memory, context window limits, and a save immediately or lose it philosophy.
Observability for AI Agents Is Broken. Here's What We Built Instead.
Standard dashboards don't work for LLM traces. We built an AI assistant that lets you ask questions about your agent's behavior in plain English - natural language to SQL queries against Logfire data.
Ship a Production AI App in 5 Minutes: FastAPI + Next.js + 20 Integrations
One CLI command, one production-ready stack: JWT auth, WebSocket streaming, Pydantic AI agents, PostgreSQL, Redis, Docker, and 20+ more integrations out of the box.
Task Planning for AI Agents: Dependencies, Events, and Hierarchical Todos
Why agents need structured planning, how subtasks and cycle detection work, and a PostgreSQL backend for multi-tenant production deployments.
Your AI Agent Forgets Everything After 50 Messages. Here's the Fix.
SummarizationProcessor vs SlidingWindowProcessor - two strategies for keeping your agent's memory alive when the context window fills up.
Pydantic AI vs LangChain vs LangGraph vs CrewAI: Which Framework to Choose?
A comprehensive comparison of Python AI agent frameworks for 2026. Pydantic AI, LangChain, LangGraph, CrewAI, and DeepAgents — when to use each one.
Ready to ship your AI app?
Pick your frameworks, generate a production-ready project, and deploy. 75+ options, one command, zero config debt.