aggregate intellect

Cohort 1

Cohort 2409

Cohort-2501

Cohort-2505

Cohort-2507

2510

2601

2603

2605

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

Agentic Buildcamp - A Cognitive Gym for Building AI Agents — using AI Agents

Sr Data Engineer

Photonics Researcher

Product Manager

Software Developer

Game Developer

Director, Risk Models & Data Science

Manager, Data Scientist

Dev Lead

Researcher

You're already trying to build something. Agentic Buildcamp is where pragmatic builders - developers, founders, and operators - ship a real AI agent using the KnowledgeOps methodology: 12+ guided workflows that take you from problem framing to production, delivered through Sherpa-B, an MCP server that connects to your CLI coding agent (eg. Claude Code). You learn by building, using the same agentic process you're learning to build with.Note 1: 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 program.Note 2: If you are interested in a mentorship version of this program, reach out to <a target="_blank" rel="noopener noreferrer nofollow" href="https://mailto:bootcamp@ai.science">bootcamp@ai.science</a>🟢 WHAT WILL I BE ABLE TO BUILD?You’ll learn to design, build, evaluate, and deploy agentic systems, and integrate required tools. By the end of the program, you'll have a working application ready to showcase in a public demo.▶️ <a target="_blank" rel="noopener noreferrer nofollow" href="https://tinyurl.com/llm-agent-demos">Playlist of previous public demos</a> 🟢 WHAT SHOULD I EXPECT TO HAPPEN DURING?This is a 3-sprint product development + 1 week of prep for the public demo.🖌️ SPRINT 1 - DESIGN (wk 1 &amp; 2)🔨 SPRINT 2 - DEVELOP (wk 3 &amp; 4)🚢 SPRINT 3 - DEPLOY (wk 5 &amp; 6)🎭 PUBLIC DEMO (wk 7)Sprint demos will be live and interactive.

Self-directed program where builders ship real AI agents in 7 wks in Claude Code

Ship a Real Agentic AI Application

Experience Learning via Building with KnowledgeOps Methodology

Obtain Assets and Artifacts that Will Super-charge your Building

Most participants fail because they're not there to build. Outside of that we don't expect you to bring much prior experience 

Lots of enthusiasm to build

You will use a CLI tool (eg. Claude Code) as the primary way to learn and build (we provide resources for this)

Claude Code

Since we use coding agents heavily, you need good version control set up (we provide resources for this)

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.

Building a Shared Human–AI Memory System

Amir Feizpour

Founder @ Aggregate Intellect

Hugo Mailhot

CoreNLP Lead @ Coveo

Why most AI workflows break down over time and how memory changes the interaction model.

From Stateless to Stateful AI

How to structure notes so they are both human-readable and usable as machine context.

Designing a Memory Backbone

Turning personal notes into reusable context for research, projects, and collaboration.

Dual-Use Knowledge Systems

Applying shared memory to research synthesis and mapping complex professional ecosystems.

Practical Use Cases

Strategies for keeping memory systems accurate, relevant, and useful over time.

Maintaining and Evolving Memory

Building AI Agents: Bootcamp 2605 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

Adaptive Research Discovery with Obsidian and Agent Skills

Percy (Boqi) Chen

Assistant Professor @ University of Ottawa

Why related-work discovery must adapt as the project direction changes.

Research Relevance Is Dynamic

How Obsidian notes and wikilinks can provide structured context for AI-assisted research.

Using Notes as Project Context

How Python and the Obsidian CLI can be combined into a reusable research helper.

Building an Agent Skill Workflow

Techniques for gathering related work based on evolving project context rather than fixed keywords.

Context-Aware Literature Discovery

How the same process can surface what has changed in the project over time.

Summarizing Project Drift

Spec Stacking & Software Factories

Owen Zanzal

Principal Cloud and Agentic Ops Engineer @ Shoplogix

Why prompts alone fail and how specs create enforceable guarantees for AI systems.

From Prompts to Contracts

How to decompose engineering practices into composable, layered specifications.

What Spec Stacking Is

Using ADRs, BDRs, and verifiers to connect architecture, behavior, and runtime validation.

Bridging Design and Execution

How structured specs turn AI into a repeatable system for producing reliable software.

Building a Software Factory

Practical approaches for embedding spec-driven workflows into existing pipelines.

Integrating into CI/CD

Harness Engineering: How Claude Code/ Codex/ Gemini CLI work

Mohsin Iqbal

Sr. MLE @ Alethia AI

The difference between agent tools (e.g., Claude Code) and the model that powers them.

Learn directly from aggregate intellect