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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

This isn't just another course. You'll walk away with tangible assets that advance your career and concrete skills that set you apart.

Founder at Aggregate Intellect

Amir Feizpour, PhD

10+ years in AI and Product Development

AI Agents for Pragmatic Builders - Claude Code, LangGraph, n8n

Photonics Researcher

Product Manager

Software Developer

Game Developer

Director, Risk Models & Data Science

Manager, Data Scientist

Dev Lead

Researcher

founder of my company

Join my next <a target="_blank" rel="noopener noreferrer nofollow" href="https://calendly.com/amirfzpr/agents-office-hour">Agents Office Hour</a> and ask about this bootcamp. 🟢 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. 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 🟢 I SEE! SO, WHAT SHOULD I EXPECT TO HAPPEN DURING?Think about it like this: 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)

Mentorship Program to Help You Build an Agent-based MVP

How to identify opportunities for building AI agents

A Complete AI Agent Application

Real-World AI Agent Skills

Systematic Agent Development Process

Coding co-pilots

No-code App Building

Python Coding

Biz or Tech Entrepreneurs - You want to build an agentic MVP to test the feasibility of your startup idea.

Hands-on Product or Operations Managers - You want to build an agentic MVP to explore a new feature in your existing product / process

Developers, Data Engineers, Data Scientists - You want to build an agentic MVP to demonstrate your skills for career progression purposes.

Claude Skills - A Mental Model for Builders

Amir Feizpour

Founder @ Aggregate Intellect

Mohsin Iqbal

Sr. MLE @ Alethia AI

A conceptual breakdown of skills beyond surface-level documentation.

What Agent Skills Really Are

How skills are discovered, loaded, expanded into prompts, scoped, and executed.

The Skill Lifecycle

How Claude integrates skills into its reasoning process and decision-making.

Reasoning and Behavior Shaping

Frameworks that make complex agent systems easier to reason about and debug.

Mental Models for Agent Design

Building AI Agents: Bootcamp 2601 Public Demo

What agentic systems can be built in 7 weeks

Skills necessary to build agentic systems

Tool stack involved in building agentic systems

How our 7-week program helps you build an agentic system

How you can go from a vague idea to a working MVP

Build Agentic Apps Using Claude Code & Bootcamp Info Session

Assess if agentic approach is appropriate for your use case.

Design agentic workflow for your use case.

Implement your agentic workflow using Claude

Leave with some workflow files you can immediately use

Learn more about our 7-week program to help you build

Agent Memories

Suhas Pai

CTO @ Hudson Labs

Enabling efficient memory hierarchy for agents

Context engineering basics

Memory architectures

Designing ethical AI systems: A hands-on workshop

Lena Shakurova

Founder @ ParsLabs

Learn a structured, repeatable process for mapping ethical risks to system design decisions.

Applied Ethical Frameworks

Identify potential harms in data use, inclusivity, and power imbalance before they reach production.

Spotting Hidden Risks Early

Translate ethical insights into technical and architectural improvements for your current or future projects.

Design Changes for Trustworthy AI

Building AI Systems with DSPy - Beyond 101

Ian Yu

MLE @ Rezolve AI

How DSPy connects prompts, programs, evaluation, and optimization into a unified workflow.

DSPy as a System-Building Tool

Practical patterns for composing DSPy modules into agentic applications.

From Components to Agents

Using metrics and feedback loops to guide system behavior and improvements.

Evaluation-Driven Development

How DSPy’s optimization work and is it actually used?

Auto-Optimization in Practice

Create and Transfer AI Coding Skills Across Your Projects

Ryan Smith

Ryan Smith is CEO at Smith Horn Group

Agents, skills, MCPs, and subagents, and when to use each

How to unpack and evaluate any skills

Repeatable process for transferring skills between projects

Security considerations people miss when adopting skills

VS Code setup and configuration to connect everything

Evolutionary LLM Systems for Code Optimization

Dmytro Nikolaiev

Dmytro Nikolaiev is a Machine Learning Scientist at ChainML (Theoriq)

Literature review of LLMs for code optimization

Productive exploration of code optimization

Where LLMs can improve perfomance

Evaluation as the engine: writing task-aligned metrics

Build an Agentic App (Part 2/2): Claude Code, n8n, LangGraph

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

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