Why Agent Evals Miss What Production Catches
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Join us at AGNTCon + MCPCon NA 2026 October 22 & 23rd in San Jose: https://hubs.la/Q04gbXLb0
An LLM can return valid JSON that your application still can’t use. It can accept a malicious prompt without complaint, break a schema on the...
In this article, you will learn how to choose the right agentic AI framework for your production system by working through a structured decision-tree based...
Compare six open-source AI agent frameworks by language, workflow control, tools, and use case, including Mastra, LangGraph, CrewAI, and Pydantic AI.
Claude Agent SDK puts Claude Code inside your application. If your product is not a coding agent, that convenience comes with architectural decisions you did not make.
12 hours after GPT-6.1 Sol launched, 3 of 10 AI libraries knew it. LlamaIndex raises ValueError; LangChain returns an empty profile. Probe inside.
Agents are still software, but traditional monitoring can't see what they actually do. A practitioner's case for treating observability as a first-class layer, and how we do it with Logfire.
Pydantic AI can run an agent on TypeSafe's Jev, a model that answers typed questions instead of writing text. Pydantic Logfire now shows each question, answer, and probability in Live view.
A large share of the AI running inside enterprise software today is not writing anything. It's not chatting with an AI chatbot, and it's not even reasoning about how to give you the correct answer.
Bring your TypeSafe key to Pydantic AI Gateway and call Jev through the System One API, with metered cost, guardrails, and the same gateway key you use for every other model.
Use Jev for categorical judgments, probabilities, and numeric rubric scores in Pydantic Evals, then track the results in Logfire without a per-score fee.
confident-trace is our new Python and TypeScript SDK for tracing production AI applications. Here's why we're separating it from DeepEval and what that means for your stack.
Image generation is now part of Pydantic AI. Here's how to use it, why we added it, and the contributor conversations that helped it happen.
AWSLambdaDurability checkpoints every model request, tool call, and MCP call as an AWS Lambda durable step. An invocation that times out or gets retried resumes from the last completed step instead of paying twice for work the agent already did.
Frontier models are changing the words in our codebases, and the change spreads from one model to the next. Evidence from GitHub, and a Pydantic AI Capability that pushes back.
You.com ships as two capabilities in Pydantic AI Harness. YouSearch gives an agent web search with excerpts and page reads, YouResearch gives it cited answers and multi-step research, and both hand your application structured citations it can render without parsing text.
Give an AI agent persistent memory as a filesystem in SurrealDB: computed file paths, fused full-text and vector search, and RBAC in a single PERMISSIONS clause
Realtime speech-to-speech support in Pydantic AI: the same agent, tools, and message history you already have, now over a live voice call. Provider-agnostic across OpenAI, Azure OpenAI, Gemini Live, and xAI, with browser WebRTC, server-side tools, gateway routing, and Logfire tracing.
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