aggregate intellect

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Cohort 2409

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Cohort-2507

2510

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

Game Developer

Director, Risk Models & Data Science

Manager, Data Scientist

Dev Lead

Researcher

founder of my company

Associate Architect

Design Leader

Postdoctoral Fellow

Principal product manager 

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 Agents: Bootcamp 2510 Public Demo

Amir Feizpour

Founder @ Aggregate Intellect

What agentic systems can be built in 7 weeks

Skills necessary to build agentic systems

Tool stack involved in building agentic systems

How to Spot/Validate High-Potential Agentic AI Opportunities

Jason Dea

Head of Product @ Koru

How to ensure your AI idea solves a genuine problem, not just a shiny use case.

Grounded Problem Validation

Why generative AI removes old barriers (e.g., data normalization, rigid APIs) and how that expands viable product ideas.

Recognizing Qualitative Shifts

How to decide if an “agent” really adds value - or if a simpler automation would suffice.

Evaluating Agentic Potential

Evaluating AI Agents

Samuel Dion-Girardeau

CTO at Tilt

Evaluating AI in markets is tough since no single "right" answer exists. Success requires creative metrics.

Measuring AI in Uncertain Domains

Beyond F1 scores, using market-centric metrics like correlation helps align AI behavior with financial realities.

Going From Accuracy to Market Relevance

Defining "good enough" using tools like MLflow and Langchain/ Langgraph matters; metrics must stand up to scrutiny.

How to Use Meta-Evaluation and Practical Tools

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

Mykola Burynok

Senior Software Engineer @ Kima Inc.

Build the backend in n8n and frontend in Cursor

Use AI co-pilots (eg. Cursor) to add code blocks to your app

Test your app to improve its performance using Claude

Build an Agentic App (Part 1/2): Design Using Claude Code

Assess if agentic approach is appropriate for your use case.

Design agentic workflow for your use case.

Implement your agentic workflow using Claude

De-Risking LLM Model Switches w Evals & Prompt Optimization

Hugo Mailhot

CoreNLP Lead @ Coveo

How consistent evaluation frameworks reduce risk in high-stakes LLM migrations.

Establishing Reliable Evals

Using evals as a foundation to systematically improve prompts and model behavior.

Automated Prompt Optimization

Lessons from migrating Coveo’s flagship RAG product to new LLMs multiple times per year.

Scaling RAG Across Models

Context Tuning for LLMs

Jack Lu

PhD Student @ Agentic Learning AI Lab (NYU)

Dr. Mengye Ren

Head @ Agentic Learning AI Lab (NYU)

Context Tuning starts prompts with real task demos, not random tokens, tapping into LLMs’ in-context learning ability.

Smarter Prompt Initialization

By leveraging task-specific context, models adapt faster and achieve higher accuracy across diverse benchmarks.

Boosted Few-Shot Performance

Competitive results are reached without updating model weights, making training lighter and more resource-efficient.

Efficiency Without Fine-Tuning

My Claude / Gemini / ... Second Brain

How flat files, YAML, and bash scripts create a transparent, portable workflow that you actually own—no vendor lock-in,

Why File-Based Systems Beat Proprietary Tools Every Time

Build a memory system that travels seamlessly between Claude, Gemini, and future AI tools without losing your context.

The Art of Tool-Agnostic Context Management

Design practical workflows that transform messy human input into structured outputs.

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