Liza Adams

Hello go-to-market leaders, strategists, and innovators! 👋 Thank you for dropping by to learn practical AI applications and gain strategic insights to help you grow your business and elevate your team’s strategic value.

Quick Take

Work is reorganizing around what customers need, not what our org charts say. Most people use AI teammates one at a time. But you can connect them so they work together like a real team.

• The gap between “who knows what” and “what needs to be done” disappears when AI doesn’t care about your org chart

• Expertise flows across team boundaries, organizing work around outcomes instead of departments

• More people can focus on strategic, big-picture work when AI handles the tactical execution and handoffs

• Connected AI teammates show you what this new way of working looks like in practice

What you’ll discover in this edition: How to start your first chain, what this means for teamwork, and real examples of teams reimagining work around customer outcomes.

LIVE DEMO:

I’ll show a real GPT chain in action — no slides, just AI teammates working together in real-time. You’ll see how each one builds on the last, and how the GPT Navigator suggests which teammates to pull in for the job. This is where the lightbulb goes off.

Prefer to Listen? Try the AI-Generated Podcast

For those who prefer to consume information through audio, I’ve used Google’s NotebookLM to transform this newsletter into a short podcast episode, featuring a natural conversation between two AI hosts. You can listen to the 16-min podcast here while driving, walking the dog, or doing chores. Once you hit play, give it just a few seconds then it will start.

How Work Should Flow

Right now, work follows org charts. Marketing creates content, hands it to Sales. Sales qualifies leads, hands them to Customer Success. Product builds more features, hands specs to Marketing.

Each handoff loses context, slows momentum, and creates friction for customers.

But when you connect AI teammates, expertise starts flowing where it’s needed, when it’s needed. Department lines become less important than getting the job done.

You’re seeing early infrastructure for work organizing around customer outcomes instead of functional silos.

From Tools to Systems: Where Most Teams Get Stuck

AI teammates are specialized AI tools you build and train with your team’s knowledge. These could be Custom GPTs, Claude Projects, Gemini Gems, or other specialized AI tools designed to handle specific tasks with your best practices built in. Each one is built, trained, maintained and managed by humans with their unique expertise.

Most teams move through three phases with AI:

Phase 1: Using AI as Tools – You ask questions, get answers. Faster individual tasks.

Phase 2: Guiding AI as Teammates – You build specialized AI that knows your processes. Better results through ongoing collaboration.

Phase 3: Orchestrating AI Systems – You connect multiple AI teammates so they work together. Different types of expertise combine in new ways.

Most teams are stuck in Phase 1. Some are building Phase 2. Phase 3 is where competitive advantage lives because most teams will stay stuck coordinating individual AI tools while you’re orchestrating AI systems.

Angie Hill, Sr. Vice President of Growth and Integrated Marketing at Procore Technologies, is already thinking about this shift.

“The companies that will make the biggest leaps are those that can reimagine how work flows when expertise can move freely across different internal teams and functions. More of our people need to think and work strategically and collectively at the outcome level. Connecting AI teammates begins to show us what that future looks like.”

How Chaining Works

Chaining means connecting AI teammates so they work together in sequence. Each one sees the full conversation and builds on what came before. Instead of briefing each AI teammate separately, you create workflows where expertise flows from one specialist to the next.

The image below shows how you “call” each GPT with the @mention function in the message box. It’s similar to how we tag people on LinkedIn. You can call GPTs one-by-one, as you need them, into the same conversation.

It’s a simple yet powerful feature. Probably one of the most underrated and underused features of ChatGPT despite being available since early 2024! Why has it flown under the radar? You need multiple Custom GPTs to make chaining valuable, and most people haven’t built them.

Here’s the difference in practice.

Without chaining (using each AI teammate individually) – You work with Content GPT to create an article → You take that output and start fresh with Webinar GPT → You summarize the webinar strategy for Email GPT → You give Social GPT a brief overview.

Each AI teammate starts from scratch. You spend time re-explaining context (e.g., target persona, key pain points, value props, stage in the buying journey). You upload or cut and paste outputs from one GPT into another. Details get lost.

With chained AI teammates – Content Drafter GPT (built by Sasha) creates messaging → @Webinar Buddy GPT (built by Shiloh) sees the full conversation and builds event strategy using that exact messaging → @Email Writer GPT (built by Remi) sees everything and creates sequences that support the webinar → @Social Creator GPT (built by Yuki) adapts it all for social platforms.

Every AI teammate sees the complete conversation. Nothing gets lost. Each specialist’s knowledge builds on the others. You get campaigns that combine everyone’s expertise from day one. This only works when each AI teammate is well-trained. Weak links in the chain amplify problems instead of solving them.

This is like assembling your dream team. Each GPT carries the knowledge of it’s human builder’s expertise in that area: Sasha’s content experience, Shiloh’s event strategy, Remi’s email best practices, Yuki’s social insights. Each builder is like a personal trainer who knows their athlete intimately and has trained them to peak performance. The team then works together with shared context toward the same goal.

When you connect the GPTs, you’re the coach. You set the strategy, guide the plays, and ensure responsible execution while your dream team delivers top-notch results.

Below is a sample marketing org chart showing the AI teammates and how humans can orchestrate jobs to be done by chaining the AI teammates together.

View the short demo video to see chained AI teammates in action for a campaign: pitch deck creator GPT + webinar planner GPT + email buddy GPT

Today, only ChatGPT supports teammate chaining in one conversation. But the concept of orchestrated AI teammates is platform-agnostic. The future is about designing systems where expertise flows.

The Research Behind the Shift

When you experience chained AI teammates, you start seeing how work wants to flow across knowledge areas, not department lines.

This aligns with what researchers are discovering about AI and collaboration. Ethan Mollick, Associate Professor at the Wharton School, shared insights from a Harvard study with P&G professionals. Cross-functional teams working with AI experienced something remarkable:

“You stop caring as much about the normal boundaries of your job.”

When specialists from different functions used AI, the lines between expertise areas nearly disappeared. Traditional silos broke down as AI helped people think beyond their specialized training. When specialists could access each other’s expertise through AI, project timelines shortened and quality improved because context never got lost in translation.

This is happening now. AI teammates accelerate this shift because expertise flows freely across them. When your positioning expert’s AI teammate works smoothly with your content expert’s AI teammate, you see how knowledge wants to move – not through department channels, but directly to where it’s needed.

People start organizing around outcomes rather than job descriptions.

As Maggie Miller, Senior Director of Corporate Marketing at HackerOne, puts it:

“What excites me most about chained GPTs is how they let us combine different perspectives smoothly. Instead of sequential handoffs where context gets lost, we get true collaboration where each expert builds on the others’ work. This is changing how we think about teamwork itself.”

If you viewed the demo above, Maggie’s quote will resonate. It changes how information flows, work gets done, and what becomes possible.

Start Your First Chain

Pick one workflow that typically involves multiple people and expertise areas:

• Product launch campaign

• Lead nurture sequence

• Customer onboarding process

• Event promotion workflow

Step 1: Map the expertise needed What different knowledge areas are required? Positioning, content, design, email, social, sales enablement?

Step 2: Check your current AI teammates Which ones do you already have? Which ones do you need to build? Each should capture one person’s expertise and best practices.

Step 3: Design the flow How should expertise move through the chain? What should each AI teammate see from the previous steps? Use @mentions to connect them in order.

Step 4: Test with human oversight Run your first chain with someone reviewing each handoff. You’re orchestrating expertise, not replacing judgment.

The goal is workflows where your team’s best practices combine every time, delivering results that no single person could create alone.

The GPT Navigator – Your Team’s AI Guide

As you build more AI teammates, keeping track of them becomes a challenge. Which GPT should you use for competitive analysis? How do you chain them for a product launch?

This is where the GPT Navigator comes in. Think of it as a Custom GPT that knows about all your team’s AI teammates and suggests which ones to use or how to chain them for any given project.

The Navigator asks a few questions about your project, then recommends the right AI teammate or suggests a chain sequence. It’s like having a smart assistant who knows everyone on your team and exactly what they’re good at. It helps teams reduce confusion and scale more easily.

Here’s a demo of how a GPT Navigator works:

Use this app to see examples of other workflows enabled by specific GPTs connected together.

Also check out a real-life GPT Navigator that the Dice marketing team uses. They call it AI Concierge.

Focusing on Jobs to Be Done

AI doesn’t care about org charts. It flows knowledge where it’s needed, when it’s needed. When your positioning expert’s AI teammate works smoothly with your content expert’s AI teammate, you see how expertise wants to flow across knowledge areas, not department lines.

What I’m observing with the GTM teams I work with aligns with broader trends. Microsoft’s 2025 Work Trend Index confirms that teams are forming around goals, not functions.

As I explored in my “AI is Breaking Department Silos: Moving from Org Charts to Work Charts” newsletter, chained GPTs give you early infrastructure for this shift toward outcome-driven work.

Once you experience this, you start asking different questions:

• What if teams formed around specific workflows instead of departments?

• What if expertise could flow to where it’s needed most, when it’s needed?

• What if we organized around customer outcomes instead of functional silos?

Your marketing chains are just the beginning. Imagine when this connects to sales, customer success, product. When customer workflows run with fewer handoffs and stops. When the gap between “who knows what” and “what needs to be done” shrinks.

AI doesn’t care about our silos and neither do our customers.

Your Next Steps

Pick one workflow that typically involves multiple people. Map the expertise needed. Identify which AI teammates you have and which you need to build. Then design your first chain.

The infrastructure is here. So, will you keep briefing your AI teammates one by one or orchestrate a team that builds together?

New to AI teammates? Start with these two newsletters:

• A Leader’s Human-AI Org Transformation Playbook – real case study of a team that grew from 20 to 100+ AI teammates today.

• Build Your AI Inner Circle – how to think about and create your first AI teammates

Ready to connect your AI teammates so they work together? You’re in the right place.

The Practical AI in Go-to-Market newsletter is designed to share practical learnings and insights in using AI responsibly. Subscribe today and let’s learn together on this AI journey!

For those who prefer more interactive learning, explore our applied AI workshops, designed to inspire teams with real-life use cases tailored to specific go-to-market functions.

Also check out this team transformation case study and step-by playbook of how we helped transform a lean GTM team into a human-AI powerhouse with human and AI teammates.

Or, if audio-visual content is your style, here are virtual and in-person speaking events where I’ve covered a variety of AI topics. I’ve also keynoted at many organization and corporate-wide events. Whether through the newsletter, multimedia content, or in-person events, I hope to connect with you soon.