Maven LIVE: AI Agents & Tools for Product Managers | Overview

chelsea oswald
5 days ago
4 min read

1. The Shift: From Chat AI → Work AI

Historically we’ve used AI like this:

PM → ask AI a question → AI responds.

But new AI tools allow AI to execute work, not just answer prompts.

Instead of:

PM → ask question

We are moving toward:

PM → assign task

AI → executes workflow

PM → reviews output

These systems are often called AI agents.

An AI agent is a software system that can perceive information, make decisions, and take actions to achieve a goal—often autonomously and iteratively.
Agents do not automatically have access to your data. They will need access to certain data or systems in order to perform tasks effectively. What they can do depends entirely on what access and permissions you give them. Many organizations use agents in read-only mode at first.
Example - Linear monitoring agent: Continuously monitors Linear, identifies new tickets, status changes, and blockers, and automatically posts a daily summary of project/ticket progress, new bugs created, and changes in sprint priorities.

Examples of Agent Tools

These tools allow you to create or run AI agents.

Tool	What it does	Link
Claude Code	Autonomously reads, writes, and edits code across your entire codebase	https://code.claude.com/docs/en/overview
Claude Cowork	Anthropic's desktop agent — autonomously manages files and tasks on your computer	https://claude.ai/cowork
GitHub Copilot (Agent mode)	Takes multi-step coding tasks across files, runs tests, fixes bugs autonomously	https://github.com/copilot

Note: Claude AI itself is already an agent — it can use tools, take multi-step actions, connect to external services, and operate autonomously via Claude Code. The tools above are useful when you need to orchestrate Claude alongside other systems, build custom agent pipelines, or automate workflows beyond a single conversation.

What PMs Should Try First

If you’re new to AI agents, the easiest way to experiment is to start with workflow automation tools.

Good starting point:

Claude AI

Example experiment:

Create a workflow that:

Checks Linear every morning
Sends ticket data to an AI model
Generates a short project update
Posts the summary in Slack

This is a simple example of an AI-powered workflow agent.

A Practical AI PM Tech Stack

Below is a realistic set of AI tools PMs at Later can experiment with.

You do not need to learn all of them. Think of this as a menu of tools that can help with different types of work.

LLM Interfaces (Daily Work)

These are the AI tools most PMs will interact with every day. They are useful for writing, analyzing information, and thinking through problems.

Tool	What it’s good for	Links
ChatGPT	Brainstorming ideas, writing product docs, summarizing notes	https://chat.openai.com
Claude AI	Analyzing long documents like PRDs, specs, create mock ups, write code or research

AI Coding Assistants (For Building Tools)

These tools help you build small tools or prototypes without needing engineering help in a specific code base, not just playing around.

Tool	Description	Link
Cursor	AI-powered code editor that helps write and modify code in existing projects	https://cursor.sh
Claude Code	AI that helps generate and reason about more complex codebases	https://docs.anthropic.com
GitHub Copilot (Agent mode)	Takes multi-step coding tasks across files, runs tests, fixes bugs autonomously	https://github.com/copilot
Replit AI	Online development environment where you can quickly build small apps or scripts	https://replit.com

Example things PMs could build:

quick internal dashboards
small scripts to process data
simple tools that call an API
rough prototypes of product ideas

The goal is rapid experimentation, not production-ready systems.

Workflow Automation

These tools connect different apps together and automate repetitive tasks.

For example, they can automatically move information between systems or trigger AI tasks.

Tool	Description	Link
n8n	Visual workflow builder for connecting apps and automating processes	https://n8n.io
Zapier	Popular automation tool for connecting thousands of apps	https://zapier.com
Make	Another visual automation tool for building workflows between systems	https://www.make.com
OpenClaw	AI-powered automation that can run continuously and perform more complex workflows	https://openclaw.ai

Terminal Basics

Some AI coding tools occasionally use the terminal (like Claude Code).

The terminal is simply a text-based way to interact with your computer by typing commands instead of clicking buttons.

Developers often use it because it’s a faster way to run tools, install packages, or start applications.

For example, an AI coding assistant might ask you to copy and paste a command like:

npm install

This just tells your computer to install the packages needed for a project.

You don’t need to learn the terminal deeply, but it helps to recognize a few common commands.

Helpful ones you might see:

cd   → move into a folder
ls   → list files in a folder
git  → manage versions of code
npm  → install and run packages

Beginner guide (optional):

https://missing.csail.mit.edu

Most AI coding tools will tell you exactly what to copy and paste, so basic familiarity is usually enough.

Key Mindset Shift

Old model: PM produces artifacts manually.

New model: PM supervises systems that generate artifacts.

This is less about working faster and more about amplifying output.