Production-ready AI agent templates
Stop starting from a blank file. Clone a battle-tested AI agent template, connect your tools and data, and ship a working agent in minutes. Every example includes a tested prompt, the right planning pattern, tools, memory, and guardrails.
- 12+ templates
- TypeScript & Python
- Free to clone
These AI agent templates are real, opinionated starting points — not toy demos. Each one encodes a proven pattern so you can skip the trial-and-error and focus on your data, your tools, and your domain.
An agent template is more than a prompt. It packages everything a production LLM agent needs: a reasoning model, a planning loop (ReAct, plan-and-execute, or reflection), a curated tool set, short- and long-term memory, retrieval over your own documents, and the guardrails that keep it safe in production. Browse by category below, pick the closest match, and make it yours.
Browse AI agent templates by use case
Twelve production-ready examples spanning support, research, engineering, data, sales, and multi-agent orchestration. Clone any one and deploy.
Customer Support Agent
PopularResolves tickets end to end — looks up the account, checks order status, issues refunds within policy, and escalates only the hard cases to a human.
Research Assistant
PopularGathers sources, extracts the key facts, cross-checks claims, and returns a cited brief. A perfect first single-agent template to learn tool calling.
Coding / PR Agent
NewReproduces a bug from an issue, writes a fix, runs the test suite, and opens a pull request with a clear summary for human review.
Data Analyst Agent
CodeTranslates plain-English questions into SQL, queries your warehouse, validates results, and explains the findings with charts and a short narrative.
Sales Outreach Agent
Researches a prospect, scores intent against your ICP, and drafts personalized outreach grounded in real account signals — queued for approval.
Ops / Incident Agent
Watches alerts, correlates logs and metrics, diagnoses the likely root cause, and runs a safe, approved remediation playbook with full audit logs.
Document Q&A (RAG) Agent
BeginnerAnswers questions over your PDFs, wikis, and contracts using retrieval-augmented generation and a vector store — with inline citations to every source.
Web Research Agent
Plans a search strategy, browses live pages, reconciles conflicting sources, and synthesizes an up-to-date answer the model's training data can't give.
Lead Enrichment Agent
Takes a raw email or domain, enriches it with firmographic and technographic data from multiple APIs, dedupes, and writes the result back to your CRM.
Content Writer Agent
MarketingResearches a topic, drafts on-brand copy against a style guide, fact-checks claims, and produces a publish-ready post with suggested internal links.
Meeting Notetaker
Ingests a transcript, produces a structured summary, extracts decisions and owners, and creates follow-up tasks in your project tracker automatically.
Multi-agent Research Team
Multi-agentAn orchestrator splits a question across specialist agents — searcher, analyst, and writer — then merges and reviews their work into one cited report.
Every card maps to a documented pattern. New to the space? Pair this gallery with how to build AI agents to understand why each template is structured the way it is, or explore the full library of agentic AI use cases.
Use a template in 3 steps
From clone to running agent in a single sitting. No boilerplate, no glue code.
1. Pick a template
Choose the example closest to your goal from the gallery. It arrives with a tested system prompt, a planning loop, a default model, and sensible guardrails already in place.
2. Connect your tools & data
Swap in your own API keys, databases, and integrations. Point the RAG step at your documents, or attach a vector store. Toggle which tools the agent is allowed to call.
3. Deploy & observe
Ship to a managed endpoint or your own infrastructure. Every run is traced — see each decision, token, and tool call — so you can debug, evaluate, and trust the output.
Prototype fast, harden later
Teams typically clone a template, validate it against real traffic on the free tier, then drop into the TypeScript or Python SDK to add custom tools and tighten guardrails. The template gives you a correct baseline; the SDK gives you full control.
Templates
across 7 categories
Clone to deploy
typical first run
Languages
TypeScript & Python
Traceable
every step logged
Inside the Document Q&A (RAG) Agent
A look at what one template actually does under the hood — the pattern most teams adopt first.
Answer questions over your own knowledge
The RAG template grounds every answer in your documents instead of the model's training data — so responses stay current, accurate, and citable. It is the safest action pattern to start with because it only reads.
Out of the box it chunks and embeds your files into a vector store, retrieves the most relevant passages for each question, and asks the model to answer using only that context, with a citation for every claim.
- Ingests PDFs, wikis, and docs into a vector store
- Retrieves top-k passages per query for grounding
- Cites every source so answers are verifiable
- Swaps models and embeddings without code changes
What every template gives you for free
Each example bakes in the production lessons that take teams weeks to learn the hard way.
- A tested system prompt — tuned to reduce hallucination and stay on task
- The right planning pattern — ReAct, plan-and-execute, or reflection, matched to the job
- A curated tool set — only the function calls the task actually needs
- Memory configured — short-term context plus optional long-term recall
- Guardrails in place — input validation, allow-lists, and human-in-the-loop checks
- Built-in observability — full tracing of decisions, tokens, and tool calls
- SOC 2-ready defaults — least-privilege tool access out of the box
- Code examples — matching TypeScript and Python snippets in the docs
AI agent templates, answered
AI agent templates are pre-built, production-ready starting points for common agentic use cases — like customer support, research, or coding. Each template bundles a tested prompt, a planning pattern (such as ReAct or plan-and-execute), the right set of tools, memory configuration, and guardrails. Instead of wiring an agent from scratch, you clone a template, connect your own tools and data, and deploy.
Clone a template and ship your first agent
Pick a production-ready example, connect your tools, and deploy in minutes. Free to start — no credit card required.