Agentic Blueprints 27
Filters
Deep Research
Splits a hard question into sub-questions, researches them in parallel to keep the wall-clock low, then synthesizes one brief with citations.
Research Digest
Multi-source sweep, dedupe, then synthesize a cited brief. Runs on a schedule.
Company Research Team
A research team combines web search with live financial data to produce a company analysis: business, stock history, and outlook.
Multi-Agent Researcher
A compact research team — searcher, analyst, writer — that turns a question into a structured research write-up.
Domain Deep Research Agent
A deep-research app that decomposes a domain question, researches the pieces, and synthesizes a cited report.
AG2 Adaptive Research Team
An AG2 research team with sequential handoffs plus routing and fallback — the flow adapts when a step comes back weak.
LATS (Language Agent Tree Search)
Monte-Carlo tree search over agent actions: generate candidates, reflect and score them, expand the best branches until one solves the task.
Agents SDK Research Bot
OpenAI's Agents SDK research flow: a planner derives searches, they run in parallel, and a writer synthesizes the report.
Financial Research Agent
Six agents produce a verified financial research note: planner, searcher, fundamentals and risk analysts as tools, writer, then a verifier.
Literature Review Team
Search agents pull papers from the web and arXiv, an analyst reads them, and a reporter writes the literature review round-robin.
AI Real Estate Agent Team
A property-search team: agents gather listings, analyze fit against the buyer's criteria, and assemble a recommendation report.
Stock Analysis Crew
Financial analyst, research analyst, and investment advisor agents dig through SEC filings and news to produce a full stock analysis.
Meeting Prep Crew
Researches the people and companies you're about to meet and compiles a briefing so you walk in knowing who's across the table.
Supervisor Team
A supervisor decides who works next — a researcher who searches or a coder who edits the repo — and assembles the result when the work is done.
Agentic RAG
Retrieval that doesn't trust its first search: it grades the results, rewrites the query when they're weak, and only answers once the context is good.
AI Finance Agent Team
A two-agent finance desk: a web-search agent for news and context, a finance agent pulling real market data through YFinance.
Swarm Support Bot
A two-agent support bot: a user-interface agent talks to the customer while a help-center agent answers from docs in a vector store.
Adaptive RAG
Routes each question to the right retrieval strategy, grades what comes back, and falls back to web search when the index can't answer.
Reflexion
An answerer that critiques itself with citations: draft, self-review for missing and superfluous content, search to fill gaps, revise.
Plan-and-Execute (LangGraph tutorial)
The original plan-and-execute notebook: a planner writes the step list, an executor works through it, and a replanner revises as results come in.
Multi-Agent Collaboration
A researcher agent and a chart-generator agent divide a task and route work between themselves until the answer is a finished chart.
Corrective RAG
Grades retrieved documents for relevance and, when they fail the grade, falls back to web search before answering.