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This document serves as a guide for developing your agentic product. It is designed to help you systematically define your product's goals, requirements, and implementation strategy. By working through each section, you will refine your product idea, identify potential challenges, and develop a comprehensive plan for building and deploying your solution.

Agents Playbook v2506

This document serves as a guide for developing your agentic product. It is designed to help you systematically define your product's goals, requirements, and implementation strategy. By working through each section, you will refine your product idea, identify potential challenges, and develop a comprehensive plan for building and deploying your solution.

Agents Playbook v2504

Are you interested in building LLM Agent Products, but unsure where to begin, or if you have the necessary background knowledge? We have curated this learning path using 70+ hours of (mostly) free resources that you can use to:<ol><li>Get started on your journey of building LLM Agent Products</li><li>Prepare to get the most of this course or similar ones, and</li><li>Evaluate areas where there's a gap in your knowledge</li></ol> After entering your email, you will be directed to a Miro Board. Contact maven@ai.science if you have any issues with this resource.

LLM AGENTS - Learning Path

Design, develop, deploy, and demo an LLM agent application in 7 weeks!

Amir Feizpour, PhD

10 yrs in NLP, Founder of AISC - Community of 5k AI devs and founders

Build Multi-Agent Applications - A Bootcamp - LangGraph, Cursor, n8n

Postdoctoral Fellow

Principal product manager 

Director of Product Design

Founder

AI Strategist 

Principal 

NOTE 1: The price shown on this page is in _USD_.NOTE 2: Check out the incentive program on this page for ways to save money.NOTE 3: LangGraph, Cursor, and n8n are the default tools we use, but you are not constraint to those You can book me to talk about this bootcamp or anything else AI / career / startup related:https://calendly.com/amirfzpr/20min-ama 🟢 WHAT WILL I BE ABLE TO BUILD IN THIS BOOTCAMP?You’ll build a functional application powered by LLM agents to automate a workflow of your choice. Along the way, you'll learn to design agent workflows, and integrate required tools. By the end of the program, you'll have a working application ready to showcase in a public demo. You can see this playlist for examples of what previous students built: https://tinyurl.com/llm-agent-demos 🟢 HOW WILL YOU HELP ME BUILD APPS LIKE THESE IN JUST 7 WEEKS?This program is all about learning by doing. You do a real project, applying concepts you learn about AI agents with our expert guidance. Specifically:👨🏽‍🏫 1:1 sessions with the us to help you think through bigger picture questions👨‍🎓 Async and sync sessions with a dedicated mentor for constant support, code reviews, and real-time feedback We also provide the "agents playbook" a step by step guide for building agentic systems with lots of hints, tips, and resources. 🟢 OK! THAT DOES SOUND FUN, BUT HOW DO I KNOW IF I HAVE THE PRE-REQUISITES?We will provide tutorials and curated material that can help you build regardless of how you want to approach it (coding, vibe coding, or no-code tools). So what you really need to be successful in this bootcamp is a lot of desire to build and not much else. You could also leverage our freely available playbook to prep beforehand and come ready (scroll down on this page). 🟢 HMM! SO I DON'T NEED TO BE A CODER?If you are, then your freedom to build what you want will definitely increase. However, we have seen people do successful projects during the bootcamp using no-code tools like N8N, LangFlow, Dify etc. We have also seen folks "vibe coding" using Windsurf, Cursor, Co-pilot etc.There are options! The question is, are you ready to build? 🟢 I SEE! SO, WHAT SHOULD I EXPECT TO HAPPEN DURING?Think about it like this (since we're developing a product here, eh?): This is a 3-sprint product dev + 1 week of prep for the public demo.🖌️ SPRINT 1 - DESIGN (weeks 1 &amp; 2)🔨 SPRINT 2 - DEVELOP (weeks 3 &amp; 4)🚢 SPRINT 3 - DEPLOY (weeks 5 &amp; 6)🎭 PUBLIC DEMO (week 7)In each sprint, you communicate your progress or blockers on Slack, you collaborate on your designs / code on GitHub, you show up to provide weekly project updates and get feedback, and finally you do an end of sprint demo. 🟢 OK! HOW WOULD I KNOW IF I'M MOVING IN THE RIGHT DIRECTION?You will get feedback async via Slack and other platforms we use, and also you join weekly group office hours, and when you need you can book the mentors for a 20 min 1:1 call.In addition, each sprint will wrap up with a "sprint demo" where you can show what you've done up to that point, and your peers and the mentors will provide feedback. 🟢 WHAT IF I DON'T HAVE A PROJECT IDEA?We provide a default project and 3 series of tutorials that provide various ways that project can be implemented using:🤃 coding,🤄 vibe coding, and🤅 no-code tools. Each series is led by one of our mentors and will meet live for an hour every week to build together and you can follow along. At the end of each session, the mentor would point out ways that you can add to the project and make it your own. If you follow through and engage it's likely that you will end up with an interesting spin on the default project that you can show off in the public demo. 🟢 COOL! I'M EXCITED TO GET STARTED, AND A DISCOUNT WOULD REALLY SWEETEN THE DEAL!Glad to hear that! There are a few options:🧑🏿‍🤝‍🧑🏼 You can find a buddy or colleague and sign up together. (20% off 2-9 seats&nbsp;|&nbsp;25% off 10+ seats)✴️ We often share discount codes with communities (including AISC members - reach out to community@ai.science if you're not part of our slack). So, check in with the communities you are part of.📆 We regularly hold events and info sessions where we share flash sales discounts valid for a day or two. Join the mailing list on this page to receive notifications about those.👨🏽‍🏫 You can apply to our Incentive Program that provides up to 75% refunds (not discounts). Apply here: https://forms.gle/YnvsoREuEX35DAxv8

Mentorship Program to Help You Build an Agent-based MVP

Course syllabus

Controlling the behavior of your agents often requires coding to include various tools, memory, or orchestration.

Python Coding

If you don't want to code, you can use no-code agent studios. We will provide specific resources but general familiarity is useful.

No-code App Building

If you are planning to code (or vibe code), familiarity with one of the coding assistants (GitHub copilot, cursor, etc), is helpful.

Coding co-pilots

You want to build an agentic MVP to test the feasibility of your startup idea.

You want to build an agentic MVP to explore the new feature you want to add to your existing product

You want to build an agentic MVP to demonstrate your skills for career progression purposes.

This bootcamp is for you if...

At the end of this bootcamp you will ...

Grasp how multiple LLMs can collaborate with each other, get feedback from or assign tasks to humans, ad use tools to tackle complex problems

Understand and utilize the core ingredients of multi-agent LLM systems

So, you build a system but does it work? How can it be improved? Out of 100 things you can change, which one is more important to focus on?

Understand the role of evaluation in building a robust agentic system

Start from a workflow, design an agentic system for it, build it, evaluate it, find test cases to fix, repeat. You do this multiple times in the 7 weeks and those reps are how you build the mental muscle!

Leave with a worked out muscle of experimentally developing an agentic system

Building AI Systems: Architecture, Team, and Trade-offs

Amir Feizpour

Founder @ Aggregate Intellect

Ian Yu

MLE @ Rezolve AI

how team structure shapes AI system design.

how maintenance needs affect architectural choices.

how to build AI services with future flexibility in mind.

Better RAG using Relevant Information Gain

Marc Pickett

AI Researcher @ Emergence AI

about balancing diversity and relevance in retrieved passage

how relevant information gain can optimize retrieval

how this approach achieves SOTA results on benchmarks

Building AI Agents: Bootcamp 2507 Public Demo

What agentic systems can be built in 7 weeks

Skills necessary to build agentic systems

Tool stack involved in building agentic systems

Build An Agentic App - Bootcamp Info Session

The types of agentic apps you can build in our bootcamp

How we help you build agentic apps

Hint: coding (eg. LangGraph), no-code (eg. n8n), and vibe coding (eg. Cursor)

What kind of implementation approaches we help you with

Anatomy of a Deep Research System - Part 2 - Evaluation

Suhas Pai

CTO @ Hudson Labs

how deep research systems retrieve and generate reports

what components power agentic research workflows

which design patterns shape current system architectures

Anatomy of a Deep Research System - Part 1 - Architecture

Practical Design Patterns for RAG

Omid Omidi

RAG alone is not sufficient for robust product performance

RAG + orchestration, routing, and external APIs = real world

Integrating RAG into production pipelines and biz workflows

Overview of Graph Augmented LLM Systems

Percy Chen

PhD Candidate, McGill University

how graphs enhance retrieval-augmented generation

why graph design is critical for system performance

NodeRAG, GraphRAG and LightRAG

Making LLMs reliable: How to test your LLM blocks in n8n

Lena Shakurova

Founder @ ParsLabs

A simple way to create test sets for your LLM blocks in n8n

How to build a testing workflow inside n8n

Refining prompts in n8n to get  repeatable results

Build an Agentic App: LangGraph + Cursor + n8n - Part 2/2

Mykola Burynok

Senior Software Engineer @ Kima Inc.

Refine design of your agentic system based on early feedback

Improve your no-code implementation or build by coding

Make your app robust using verification and feedback loops

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