chatgpt

ChatGPT as a Social Network? Learning From Past Mistakes

Learn from past failures like Google+ and wins like Twitch. Discover how AI could enhance collaboration, publishing, and networking by solving real problems—without forcing social.

Mike Parsons

07 Mar 2025 • 9 min read

ChatGPT has been teasing the idea of either buying X (formerly Twitter) or launching its own social network—a big, bold, and potentially doomed move if history is any indication.

Because let’s be honest: we’ve seen this story play out before. Google+ tried to force a social network into existence, and it flopped. Hard.

Why? Because it didn’t solve a problem worth solving.

It wasn’t just a bad product—it was a pointless product. Nobody needed it. Nobody wanted it. It wasn’t filling a gap or enhancing an existing behavior. People already had Facebook, Twitter, LinkedIn, and email. Adding another social layer didn’t improve life; it just added friction.

But not all tech companies fail at “going social.” Amazon and Twitch? That worked. But not because Amazon tried to make a social network out of thin air. Instead, it built social features around an existing community, integrating Prime Gaming and the Twitch Partner Program to give gamers and streamers real value.

So, if OpenAI wants ChatGPT to go social, it needs to solve an actual problem—not just slap on a "social" button and hope for the best.

1. ChatGPT + Google Drive = AI-Powered Collaboration

Problem: AI is great at generating ideas, but workflows are scattered.

Millions of people already use ChatGPT to brainstorm, draft content, analyze data, and organize thoughts. But once you get that AI-generated output, where does it go?

For most people, it ends up in:

A Google Doc that gets buried in their drive
A Notion page that nobody looks at
A Slack message that disappears into the void

That’s a problem worth solving.

Solution: Integrate ChatGPT directly with Google Drive to create an AI-powered collaboration hub.

Co-edit documents in real time with AI-powered suggestions
Auto-tag team members who might have relevant insights
Use AI to summarize, organize, and prompt next steps

Instead of trying to compete with existing social platforms, this would supercharge collaboration—making AI a core part of team workflows rather than just a one-off assistant.

Why it would work: AI would enhance existing behaviors instead of disrupting them, fitting seamlessly into how people already work. There would be no need to learn a new platform or build a new habit.

2. ChatGPT + Medium = AI-Enhanced Publishing

Problem: People are creating more content than ever, but it lacks depth, accuracy, and discussion.

Let’s face it—AI-generated content is exploding. But a lot of it is low effort and unverified. People are churning AI-written LinkedIn posts, blog articles, and newsletters without fact-checking, citing sources, or adding unique insights.

That’s a problem worth solving.

Solution: Connect ChatGPT to Medium for a frictionless AI-powered publishing and discussion platform.

One-click publishing from ChatGPT to Medium
AI fact-checking and citation suggestions before publishing
AI-powered discussions where readers can ask follow-up questions and dive deeper into topics

This wouldn’t just be another content feed—it would be a knowledge hub where AI enhances the writing process and encourages meaningful conversations.

Why it would work: It solves a real problem in content creation. People already use AI to write but need better tools to ensure their writing is accurate, engaging, and interactive.

3. ChatGPT + LinkedIn = AI-Powered Matchmaking

Problem: LinkedIn is bloated, noisy, and not great at real networking.

LinkedIn was once a great professional network. Now? It’s turning into Facebook Work Edition—full of:

Cringe-worthy humblebrag posts
Generic thought leadership that’s just AI-generated fluff
Random connection requests with zero context

That’s a problem worth solving.

Solution: Use AI for actual networking, not just passive scrolling.

AI-powered introductions based on shared goals, not just “People You May Know” randomness
An AI-optimized content feed that filters out the junk and surfaces only what’s truly relevant to your industry
AI-assisted messaging that helps you craft intros that sound human

Instead of another “social network,” this would be an AI-powered career accelerator—helping people find real connections and opportunities faster than ever.

Why it would work: LinkedIn has zero competition, and ChatGPT could create a more dynamic, intelligent alternative that helps people advance their careers.

Google+ failed because it didn’t solve a real problem. It forced social networking where it wasn’t needed.

Amazon and Twitch succeeded because they integrated social features into platforms with engaged users and clear purposes.

If OpenAI is serious about making ChatGPT social, it must follow the Twitch model, not the Google+ one. Instead of creating a social network from scratch, it should:
✅ Enhance workflows with AI-powered collaboration
✅ Make publishing more innovative and more interactive
✅ Reinvent professional networking with AI-driven matchmaking

That’s how you solve problems worth solving.

The Fit Model: How to Avoid Building the Next Google+

Tech history is full of significant, expensive failures—Google+, for example. Meanwhile, companies like Amazon and Twitch succeeded because they added social elements that made sense instead of forcing them.

That’s where the Fit Model comes in. It’s a straightforward, practical approach to ensuring your idea isn’t just enjoyable, practical, wanted, and profitable. The model consists of three key stages:

Problem-Solution Fit – Are you solving a problem worth solving?
Product-Market Fit – Do people want this?
Business Model Fit – Can you make money without burning through investment funds?

How do you apply this model to avoid launching the next big tech disaster and instead build something that lasts? Let’s break it down.

Step 1: Problem-Solution Fit – Are You Solving a Problem Worth Solving?

Before you start building anything, take a step back and ask:

Does this fix a real problem?
Would people care if it disappeared tomorrow?

If the answer to both is unclear, you might already be heading in the wrong direction.

How to Find a Problem-Solution Fit:

Identify the core problem
- What is frustrating or inefficient in the current landscape?
- Are people actively searching for a better solution?
Find out who has this problem
- Who is the ideal customer?
- Do they experience this problem frequently enough to care?
Test your assumptions in the real world
- Have direct conversations with potential users.
- Observe how they are currently trying to solve the problem.
Make a simple, testable version of your solution.
- Create a quick prototype, even if it is just a landing page or a basic version of the concept.
- Get feedback from real users before committing to complete development.

If people do not immediately see value or feel excited about the solution, it is a sign that adjustments are needed before moving forward.

Example: In Can ChatGPT Succeed as a Social Network?, we explored how OpenAI could avoid Google+'s mistakes by integrating AI-powered collaboration into existing workflows instead of launching an entirely new social platform.

Step 2: Product-Market Fit – Do People Want This?

Once the problem and solution are aligned, the next challenge is determining whether people will actively use and pay for the product.

How to Find Product-Market Fit:

Measure real engagement, not polite feedback
- Are users coming back to use the product consistently?
- Are they recommending it to others without being asked?
Identify your most substantial user base
- Who gets the most value out of your product?
- How can you refine the messaging and features to attract more of these users?
Analyze market demand
- Is this solving a common problem, or is it a niche issue?
- Who are the competitors, and why would users switch to your solution?
Run small-scale tests
- Launch a waitlist or an early-access program.
- Run small ad campaigns to gauge interest.
- Offer pre-orders or early sign-ups to test commitment.

If people engage and keep returning, that signifies product-market fit. If not, it may be time to refine the product or target a different audience.

Example: In Can ChatGPT Succeed as a Social Network?, we suggested that instead of launching a standalone platform, OpenAI should integrate ChatGPT into Google Drive, Medium, and LinkedIn. These are platforms where AI-powered tools would provide clear and immediate value.

Step 3: Business Model Fit – Can You Make Money Without Relying on Endless Investment?

Even if people love a product, it does not mean it will be a sustainable business. The next step is determining whether it can generate revenue consistently.

How to Find Business Model Fit:

Select a revenue model that aligns with user behavior
- Will people pay for this through subscriptions, one-time purchases, or usage-based pricing?
- Is the pricing reasonable for what it offers?
Understand customer acquisition costs (CAC) vs. lifetime value (LTV)
- How much does it cost to acquire a paying customer?
- How much revenue will that customer bring over time?
- The business model is not sustainable if the cost to acquire a customer exceeds the revenue.
Optimize growth channels
- Which marketing channels bring in the most cost-effective users?
- How can the acquisition cost decrease as the business scales?
Ensure retention and upselling opportunities
- Are customers staying engaged and renewing their subscriptions?
- Can additional features, upgrades, or services increase revenue per user?

If the business only survives by constantly raising investment rounds, it is not built for long-term success. A strong business model ensures that revenue exceeds costs.

Example: In Can ChatGPT Succeed as a Social Network?, we explored how OpenAI could monetize AI-powered collaboration through premium features, networking tools, or enhanced content distribution services instead of relying on traditional ads.

Final Thoughts: How to Avoid Building the Next Google+

The Fit Model serves as a practical guide for validating business ideas. Following these steps helps prevent common pitfalls and ensures that resources are invested in something that has real potential.

If you skip a step…

No Problem-Solution Fit → You risk building something no one needs.
No Product-Market Fit → You might create an incredible product, but no one will stick around.
No Business Model Fit → You gain users but struggle to turn a profit.

Problem-Solution Fit: Does the world need another social network? → No, but AI-powered workflows could be highly valuable.
Product-Market Fit: Do people actively use and benefit from AI-driven collaboration? → Testing integrations with Google Drive, Medium, and LinkedIn can determine demand.
Business Model Fit: Can OpenAI monetize this effectively? → Premium AI-powered productivity tools and networking features could offer sustainable revenue.

By following the Fit Model, OpenAI can avoid repeating Google+'s mistakes and instead create something that enhances user experience meaningfully.