AI Agents

Wire up an orchestrator agent and specialized subagents through MCP tool servers — with working Python, task splitting, and result aggregation.

Step-by-step guide to creating a browser automation agent that observes pages, decides actions, and extracts data with LLMs.

Create a code-writing agent that generates Python, runs it safely in a sandbox, and self-corrects on errors

Automate code reviews with an LLM-powered agent that reads Git diffs and suggests improvements

Create a contract Q&A agent that pulls payment terms, termination clauses, and liabilities from any PDF automatically.

Create an intelligent cron job manager that interprets natural language schedules and handles task execution with LLMs

Create a support agent that answers from a knowledge base, checks orders, and escalates when unsure

Create agents that write and run Python to answer data questions, generate charts, and query databases from plain English prompts.

Create a conversational agent that takes plain English data requests and autonomously generates, runs, and debugs pandas transformations.

Create an agent that automatically diagnoses Python errors by analyzing stack traces and reading source code

Create a document QA agent that parses PDFs, chunks text, and answers questions with citations

Create a filesystem agent with OpenAI tools that manages local files through a secure, sandboxed agent loop.

Create an LLM-powered financial agent that pulls live market data and produces actionable analysis

Automate GitHub issue triage with an LLM-powered agent that classifies bugs, assigns priority labels, and routes to the right team.

Create a log analysis agent that uses LLMs and regex tools to find patterns, errors, and anomalies in log files

Turn recorded meetings into action items and summaries using Whisper transcription and LLM agents

Give your AI agent a real memory system that stores, searches, and recalls past conversations using vector embeddings.

Create a FastAPI agent that catches Prometheus alerts, pulls relevant metrics, and gets an LLM to explain what went wrong

Get better LLM answers by having multiple agents debate and a judge agent select the winner

Wire up specialist agents that discover, communicate, and delegate tasks over Google’s Agent-to-Agent protocol.

Step-by-step guide to creating an agent that combines vision capabilities with tool use for image analysis and text extraction.

Learn to build AI agents that break down complex problems, manage dependencies, and automatically replan when things go wrong

Create an autonomous research agent that gathers info from the web and produces structured reports

Create an agent that searches your docs, reranks with cross-encoders, and generates grounded answers.

Create an autonomous agent that books meetings, checks availability, and sends invites with OpenAI tool calling

Ship a Slack bot that answers questions, summarizes threads, and takes actions using LLM tool calling

Create a conversational SQL agent with tool calling that inspects schemas, runs read-only queries, and refines results across multiple turns

Wire up Claude to MCP tool servers and build an agent loop that picks and calls the right tools automatically

Create a research agent that autonomously searches, reads, and summarizes web content using LLMs and search APIs

Create workflow agents with approval gates, feedback collection, and iterative refinement loops

Create an autonomous API testing agent that writes and runs HTTP tests from natural language specs

Create a testing agent that generates pytest tests, runs them, and fixes failures automatically with LLM-powered code analysis

Automate your inbox with a Python agent that reads, classifies, drafts replies, and files emails using IMAP and LLMs.

Step-by-step guide to creating an MCP server that gives AI agents access to custom tools and data sources.

Build agents that query databases, call APIs, and process results while preventing SQL injection and data leaks

Build agents that pause for human approval before taking risky actions, with working LangGraph interrupt and resume code.

Give your AI agents memory that survives restarts using LangGraph’s checkpointer system with real database backends.

Build your own reasoning-and-acting agent from scratch without frameworks, and understand every line

Create a Python agent that can search the web, run calculations, and chain tool calls autonomously

Create collaborating AI agents with AutoGen’s group chat, role-based agents, and sandboxed code execution for real tasks.

Step-by-step guide to creating reliable AI agents with LangGraph’s graph-based architecture and built-in persistence.

Ship production agents with built-in tools, custom MCP servers, hooks, and subagents in Python

Create agents that call functions, execute code, and manage conversations with persistent threads using the Assistants API.

Create teams of AI agents that collaborate on tasks using CrewAI’s role-based framework and process orchestration.

Find and fix agent loops, broken tool calls, and prompt regressions using LangSmith’s trace UI and evaluation SDK.