📰 Dev.to · Nebula

Side-by-side comparison of LangChain Deep Agents and OpenAI Agents SDK with code examples, feature tables, and a decision framework.

Build a working MCP server with two custom tools using FastMCP and Python. Copy-paste, run, connect to Claude Desktop.

Build resilient AI agents with retry, fallback, circuit breaker, and graceful degradation patterns. Pure Python code you can copy-paste today.

Compare the best AI agent memory frameworks in 2026: Mem0, Zep, Letta, Cognee, LangChain Memory, and LlamaIndex Memory.

Stop parsing messy LLM text. Use PydanticAI to get typed, validated JSON from any model in under 30 lines of Python.

Learn 4 battle-tested event-driven architecture patterns for AI agents with runnable Python code, retry logic, and production tips.

Build an AI agent that converts natural language to SQL queries using PydanticAI and SQLite — no database server required.

A practical comparison of the top 7 AI agent frameworks in 2026 — from LangGraph to CrewAI — with honest trade-offs and a decision matrix.

Build a working Model Context Protocol server with TypeScript that exposes a custom tool to any AI assistant.

Build a simple fallback chain so your AI agent switches to a backup model when the primary LLM fails. Copy-paste Python code included.

AI agents fail silently in production. Here are 5 testing patterns -- from deterministic assertions to budget tripwires -- that catch failures before your users

Connect to any MCP server from your own Python code. Discover tools, call them, and get results -- all in under 40 lines.

Most teams go multi-agent too early. Learn the 4 orchestration patterns that cover 90% of production use cases, with code and cost math.

Block prompt injection and validate agent outputs using input and output guardrails in the OpenAI Agents SDK -- full code included.

Compare the top structured output libraries for LLMs -- Instructor, PydanticAI, Outlines, Guidance, and Zod. Side-by-side on features, approach, and best use.

Your AI agent blocks for 30 seconds then dumps a wall of text. Here's the fix -- stream tokens and tool events in real time with the OpenAI Agents SDK.

OpenAI acquired Promptfoo. Here are 5 independent eval tools for testing AI agents in 2026 -- from open-source CLI to full production platforms.

Give your AI agent real capabilities. Register Python functions as tools with PydanticAI's @agent.tool decorator and typed dependencies.

Learn 4 context engineering strategies for AI agents with runnable Python code. Budget your context window, compress history, and inject tools dynamically.

Build a lightweight memory system for your AI agent in pure Python -- no frameworks, just a list and a JSON file.

Five production-tested patterns to control AI agent costs — token budgets, model routing, context pruning, circuit breakers, and caching — with Python code for

Mock the LLM layer and test your AI agent's tool routing deterministically with pure pytest. No frameworks, just 20 lines of test code.

Stop your AI agent from executing dangerous actions unchecked. Add a human approval gate to any tool call with one Python function.

Stop losing LLM responses to rate limits and timeouts. Add bulletproof retry logic to any OpenAI call with one Python decorator.