Boardy AI and the Future of Business Networking: Why Intent May Matter More Than Connections
For years, we've measured the strength of a professional network by the number of people in it.
500 LinkedIn connections.
5,000 connections.
20,000 connections.
But after building a large professional network, you eventually discover something: knowing a lot of people and knowing who you should talk to right now are two completely different things.
That's the problem that makes Boardy AI interesting.
Boardy describes itself as an AI superconnector. You actually talk to the AI about your business, what you're working on and what you're trying to accomplish. Boardy uses that context to identify people who may be worth meeting and helps facilitate the introduction.
After using it, I think the bigger idea goes well beyond another way to find people on LinkedIn.
LinkedIn built the professional graph.
Boardy is beginning to build something different:
The intent graph.
And intent may ultimately be far more useful for business development than another list of connections.
LinkedIn Knows Who You Are. Boardy Wants to Know What You're Trying to Do.
LinkedIn is extraordinarily good at answering questions about professional identity.
Where does someone work?
Where did they work before?
What's their job title?
Where did they go to college?
Who are they connected to?
What industry are they in?
That's the professional graph, and LinkedIn has spent decades building it.
But there's another question that's often far more valuable:
What is this person trying to accomplish right now?
A LinkedIn profile doesn't necessarily tell you:
“I'm looking for a strategic partner.”
“We're considering acquiring companies.”
“I need an introduction to someone at Verizon.”
“We're raising capital.”
“We need better location data.”
“I'm looking for companies that have information about wireless dead zones.”
These are intentions, not identities.
And intentions create opportunities.
Here's a Real Example
One of my businesses operates a crowdsourced map of wireless dead zones.
Imagine two LinkedIn profiles.
One says:
Founder — Crowdsourced Mapping Company
The other says:
Executive — Wireless Carrier
LinkedIn knows who both people are.
But those profiles don't necessarily explain why they should meet.
Now imagine the wireless executive tells an AI agent:
“We're trying to better understand geographic areas where customers consistently experience poor wireless coverage.”
And I tell the same AI:
“We have years of crowdsourced reports showing where consumers experience wireless dead zones.”
Now the connection becomes obvious.
The value isn't that the AI found two people in the wireless industry.
The value is that it understood what both people were trying to accomplish at that moment.
That's the intent graph.
And that's what makes this category interesting.
The Hardest Part of Business Development Isn't Finding People
I've done enough business development to know that finding someone's name usually isn't the hardest part anymore.
LinkedIn solved much of that.
The harder problem is getting someone's attention.
You identify the company.
You find the executive.
You send the LinkedIn request.
Maybe they accept.
You send the message.
Maybe they see it.
You find an email address.
You send an email.
Maybe they respond.
Executives are overwhelmed with messages, pitches, newsletters and meeting requests.
Being able to identify the right person doesn't mean you'll ever speak with them.
That's why introductions remain so powerful.
Compare:
“I'd like to add you to my professional network.”
with:
“I've spoken with both of you. Based on what you're each working on, I think you should meet.”
The second message has context.
More importantly, it has a reason.
That's What a Great Human Connector Does
We've all met people who are unusually good connectors.
You explain your business problem and they immediately say:
“You need to talk to Sarah.”
They don't search a database.
They understand your problem, remember another conversation and recognize the connection.
That's an incredibly valuable skill.
It also doesn't scale very well.
A human connector can't have meaningful conversations with hundreds of thousands of people and remember what everyone is working on.
An AI can approach the problem differently.
Every conversation provides context.
What are you building?
What problem are you solving?
What do you need?
Who are you trying to meet?
What can you offer someone else?
That's much richer information than a job title.
The Next Problem: Calendar Ping-Pong
Even after getting someone's attention, business development has another ridiculous friction point.
Scheduling.
Someone makes an introduction.
Both people respond:
“Sounds interesting. Let's talk.”
Great.
Then:
“How's Tuesday?”
“Tuesday is bad. Wednesday?”
“Traveling Wednesday.”
“Thursday afternoon?”
“Booked. How about next week?”
We've all experienced it.
A potentially valuable introduction turns into six emails just to get 30 minutes onto a calendar.
Sometimes the meeting never happens.
Boardy's ability to coordinate calendars is therefore more important than it initially sounds.
Once both people want to meet, Boardy can help find a time that works and get the meeting scheduled.
That removes an entire layer of friction.
The networking process becomes:
Need → Match → Introduction → Schedule → Conversation
Every unnecessary step between the introduction and the conversation creates another opportunity for the relationship to die.
A Great Meeting Can Still Go Nowhere
Then comes another problem I've seen repeatedly.
You finally have the meeting.
It's a good conversation.
Someone says:
“I know someone you should meet.”
Another person says:
“Send me that information.”
You identify a potential partnership.
Someone promises to make an introduction.
You agree to reconnect.
Everyone hangs up feeling like the meeting was productive.
Then everyone goes to their next meeting.
A week passes.
Who was supposed to send what?
Who offered the introduction?
When were you supposed to reconnect?
This is where a surprising amount of business development dies.
Not because the opportunity was bad.
Because nobody followed through.
Meeting Summaries Are More Important Than They Sound
This is another part of Boardy's approach that I find useful.
Boardy can be involved in meetings and preserve the context of what was discussed.
Instead of finishing a call with handwritten notes—or no notes—you can have a clear record of the conversation.
What were the major points?
What opportunities emerged?
Who agreed to do what?
What introductions were discussed?
What information needs to be sent?
What's the next step?
When should everyone reconnect?
That changes the value of an AI meeting summary.
It's not simply:
“Here's what everyone said.”
The valuable question is:
“What should happen because of what everyone said?”
That's a much more important business-development problem.
From Meeting Notes to Opportunity Intelligence
Imagine finishing a meeting and having your AI tell you:
Three opportunities came out of this conversation.
Partnership: The company expressed interest in using your data.
Introduction: The executive offered to introduce you to another company.
Follow-up: You agreed to send pricing and usage information.
That's not a transcript.
That's opportunity intelligence.
And when the AI retains that context, it becomes even more useful.
A week later, it knows the information hasn't been sent.
A month later, it remembers the introduction that was discussed.
Six months later, it still knows why these two people originally met.
Humans aren't particularly good at doing that at scale.
The Eight-Year-Old LinkedIn Connection Problem
This becomes even more interesting if you have a large LinkedIn network.
Suppose you connected with someone eight years ago.
At the time, they worked for Company A.
Since then, they've worked at Company B and Company C.
Today they're running partnerships at the exact company you're trying to reach.
Technically, you already know the person.
Practically, you've forgotten about the relationship.
There is enormous dormant value sitting inside professional networks because people can't remember thousands of connections.
Imagine asking:
“Who do I know at companies that acquire digital publishing businesses?”
Instead of simply searching current titles, an intelligent relationship agent could understand your history.
It might respond:
“You already know three people who are relevant. One of them is someone you met eight years ago who now runs corporate development at a company in this space.”
That's dramatically more useful than another search result.
Connection Count May Become the Wrong Metric
This leads to a bigger question about LinkedIn.
For years we've treated connection counts almost like professional currency.
But what does having 20,000 connections actually mean if you can't remember 18,000 of them?
AI changes the equation.
The future advantage may not be:
“I have 20,000 connections.”
It may be:
“My AI understands the context behind 20,000 relationships.”
That's an entirely different asset.
Your network stops being a static list.
It becomes searchable relationship intelligence.
Boardy Isn't Really Competing With One Company
It's tempting to compare Boardy with LinkedIn, Calendly, AI meeting assistants or CRM platforms.
But I don't think any one of those comparisons captures the idea particularly well.
LinkedIn helps you find people.
Scheduling software helps you meet them.
Meeting assistants help you remember the conversation.
CRM software helps you track the relationship.
Boardy's interesting idea is connecting those steps.
Understand what I need.
↓
Identify someone relevant.
↓
Make the introduction.
↓
Get the meeting scheduled.
↓
Understand what happened.
↓
Identify the action items.
↓
Remember the relationship.
↓
Help determine what should happen next.
The real competitor isn't one piece of software.
It's the old business-development workflow.
Business Development Is Still Remarkably Fragmented
Think about how many tools we currently use to build one professional relationship.
You search LinkedIn.
You send an email.
You ask a mutual connection for an introduction.
You exchange messages.
You send a scheduling link.
You create a Zoom meeting.
You use an AI meeting assistant.
You put notes into a CRM.
You create a reminder to follow up.
And then sometimes you still forget.
That's a tremendous amount of administrative work surrounding something very human:
Two people having a useful conversation.
AI agents can remove much of the administrative layer without removing the human relationship.
That's the opportunity.
AI Shouldn't Replace Networking. It Should Remove the Friction Around It.
This distinction matters.
I don't want AI having my relationships for me.
I want it helping me have better relationships.
Let AI remember the meeting.
Let AI coordinate the calendars.
Let AI remind me what I promised.
Let AI recognize that someone I spoke with three years ago is now relevant.
Let AI discover that two people it has spoken with are trying to solve complementary problems.
Then let the humans talk.
That's a much more compelling use of AI than automating another round of cold outreach.
From CRM to ARM: AI Relationship Management
We've spent decades building CRM systems—Customer Relationship Management software.
But most CRMs have a basic problem.
Someone has to keep updating them.
“Spoke with customer.”
“Interested in partnership.”
“Send deck.”
“Follow up in 30 days.”
Humans are inconsistent about entering that information.
AI introduces another model.
Call it:
ARM — AI Relationship Management
An AI relationship manager doesn't just store contacts.
It understands:
Who you know.
Why you know them.
What you discussed.
What they're working on.
What you're working on.
What each person needs.
What introductions were promised.
What opportunities exist.
When you should reconnect.
Who else should meet.
That's much closer to how a great human connector thinks.
What Happens When AI Agents Start Talking to Other AI Agents?
This is where the idea gets even bigger.
Imagine millions of professionals eventually having AI agents that understand their current business objectives.
My agent knows:
“Jeff is looking for strategic partners for a location-data business.”
Someone else's agent knows:
“Sarah's company is actively looking for unique location datasets.”
The agents recognize the overlap.
Both humans approve the introduction.
The agents coordinate calendars.
The humans have the conversation.
The AI captures the action items.
Another introduction emerges from the meeting.
The process continues.
Nobody searched through 500 profiles.
Nobody sent 100 cold emails.
Nobody exchanged eight emails trying to schedule a meeting.
The network understood the opportunity.
The Future of LinkedIn May Be Less About Search
This is the part I find most interesting.
LinkedIn created the professional graph.
That graph is enormously valuable and isn't going away.
But AI adds another layer on top of it.
Identity + Relationships + Intent + Conversation + Memory
The first generation of professional networking answered:
Who do I know?
Search made it possible to ask:
Who can I find?
AI lets us ask something much more useful:
Who should I talk to right now?
And then:
Why?
Can you introduce us?
Can you find a time?
What came out of the meeting?
What should I do next?
That's a very different professional network.
The Professional Network of the Future May Be Something You Talk To
That's ultimately what makes Boardy interesting to me.
It isn't another reason to collect more connections.
It's an early example of what happens when our existing professional networks become intelligent.
The hard part of business development has never been collecting names.
It's getting the right person's attention at the right moment.
Then getting the meeting scheduled.
Then having a useful conversation.
Then making sure the conversation actually leads somewhere.
AI is unusually well suited to removing friction from every one of those steps.
And that may change how we think about professional networking altogether.
The network of the future may not be something we spend hours searching.
It may be something that understands what we're trying to accomplish and helps us act on the relationships we already have—and discover the ones we don't yet know we need.
Instead of saying:
“Here are 500 people who match your search.”
the most valuable professional AI may simply say:
“I know someone you should meet.”
