Dated prediction and platform correction — October 11, 2026. This is an October 14, 2025 forecast, not evidence of a permanent gap or an established 18-month deadline. No source-defined cohort supports the 80–90%, 2–5× or 10× generalizations, and no comparable follow-up is provided. OpenAI introduced apps and the Apps SDK preview on October 6, 2025; it opened review submissions and the app directory on December 17, 2025. The original platform-history comparisons do not establish guaranteed distribution. For the fintech outcome, see the later chronology clarification. Build a recovery path for provider failure rather than aiming for collapse.
Real talk from a technical founder building AI-powered businesses
Published October 14, 2025 • Based on Founder Reality Episode 29
Also available on: Apple Podcasts • Spotify • YouTube
Three things happened this week that look completely different but tell the same story:
- Wall Street Journal published research showing AI is widening the gap between superstars and average employees
- A new breed of founders on Twitter are building distribution first, products second
- OpenAI introduced apps and an Apps SDK preview; the directory and review submissions came later
The connecting thread: We're entering a phase where the gap between people who get AI and people who don't is about to become permanent.
Permanence was my prediction. This article does not establish that a performance gap is irreversible.
The eighteen-month window was speculative, not a validated deadline for skills or business viability.
Story 1: Why AI Makes Superstars Even More Super
The Wall Street Journal just published an article that challenges everything we thought about AI leveling the playing field.
Everyone assumed AI would help average performers catch up. That junior employees could use ChatGPT to do senior-level work. That the performance gap would narrow.
I interpreted that coverage as a warning that AI need not narrow every performance gap.
I did not supply the underlying study or a comparable measure establishing a general 10× widening of performance gaps.
Here's why:
Superstars master tools faster. They understand what tools exist that most employees don't even know about yet.
Superstars have domain expertise. They can ask better questions. Remember when we talked about prompt engineering a few years ago? It's still relevant. Better prompts = better outputs.
Superstars use AI systematically. They don't just open ChatGPT and type a question. They have frameworks. They have systems. They extract way more value.
Different workers have different access, training, job constraints and uses for these tools; the labels here do not establish their motivation or capability.
The Three Types of Builders
I've spent the past three years building with AI (I started early 2023, a few months after ChatGPT launched). I've seen three distinct types of builders emerge:
Type 1: Building the Old Way (80-90% of founders)
Still using manual processes. Still hiring for every job function. Still skeptical about AI beyond basic ChatGPT usage.
They might occasionally ask "Give me a template for my hiring plan" or "How do I optimize my business?" But it's minimal. Nothing significant.
If you look at Glassdoor, Indeed, LinkedIn - people are still hiring for tons of office jobs. These business owners haven't changed their workflow at all.
Type 2: Using AI as a Tool (Most of the remaining 10-20%)
Using lots of AI tools - Claude, Gemini, ChatGPT, Cursor. But not fundamentally changing how they build.
They use AI as a reference point, not as a system. On-demand questions: "I have a question, I ask AI. I have another question, I ask AI."
They might use Cursor for some code, ChatGPT for content. They're better than Type 1, but still thinking in the old paradigm.
AI is just a tool for them, not a fundamental shift in how they operate.
This is probably you if you're being honest. It's definitely where I was until recently.
Type 3: AI Native from the Ground Up (The Future)
These founders tend to be younger - straight out of college in recent years. But it also applies to founders in their late 20s, 30s, 40s who've made the mental shift.
Every workflow is embedded with AI. Not just for the name, but because it genuinely benefits from AI technologies.
Every hiring decision starts with: "Can AI do this + contractors?" Instead of "Should we hire an employee?"
They're building products that would've needed 10 engineers with just 2 engineers, using AI for the rest. Same quality as Type 2 and Type 1, but with 80% fewer people.
Why the Gap Will Become Permanent
Here's the scary part:
The gap between Type 3 founders and Type 1/Type 2 founders won't show up for another 12-24 months.
Technology is only two years old. Everyone's revenue still looks roughly the same.
But Type 3 founders are:
- Potentially building faster; the 2–5× estimate lacks a defined comparison here
- Potentially learning faster; the 10× estimate lacks a defined comparison here
- Experimenting with new workflows; this does not establish that other builders cannot learn or adapt
We won't see the revenue differences, productivity differences, or headcount differences yet. But in a year, it's going to show up. And the gap will widen.
The two-year point is a forecast, not evidence that later learning or adaptation is impossible.
I expected workflow differences to matter. I did not establish that those differences would become permanent or that later adaptation would be impossible.
While you're figuring out "how do I better use AI tools?", they're already building their second and third companies with AI-first thinking.
My SimpleDirect Reality Check
At SimpleDirect, we have 2 engineers now. Two years ago, we had 6-8 engineers.
Going from 8 to 2 doesn't mean we're less productive. We're just as productive. Maybe more.
We've built 2-3 different products over the past two years. Thanks to GitHub Copilot, Cursor, Claude Code.
If you told me two years ago we'd be this productive with 2 engineers, I wouldn't have believed you. But AI makes it possible.
We can also pivot faster. Right now I'm giving SimpleDirect Financing a 90-day sprint to see if we can make it work with a different customer profile and distribution strategy. I'm doing this solo while my team works on another project.
That's only possible because of AI. Using Claude to draft articles for our target readers, social media posts for X and LinkedIn, brainstorming distribution strategies.
Two or three years ago? We'd need 10+ people to do what we're doing now.
If You're an Employee, This Should Excite You
The Wall Street Journal article focused on corporate employees. If you work for someone, this shouldn't be draining news.
You have two massive opportunities:
Opportunity 1: Maintain Performance with Less Time
I have friends (you probably do too) using AI to do their jobs in 50-70% of the time it used to take.
The 9am–5pm to 12pm–5pm schedule was an illustration, not a result established for every job. Measure quality, review and obligations before assuming a time saving.
What do you do with that extra 30-40% of time?
Build side projects. Work on your own startup. Learn new skills. Develop expertise.
The old excuse was: "My job is too demanding. I'm 9-5 all the time."
Actual workloads, access and employer obligations differ. A possible time saving is not permission to divert confidential work or required working time into a side project.
And before you quit your job, make sure you have:
- 6-12 months runway saved (I prefer 12-18 months)
- Stable consulting income (ideally 80-100% of your current income from 3-5 diverse clients)
- Clear validation for what you're building
Build revenue before you quit. That's critical.
Opportunity 2: Become Indispensable
Use AI to become the person everyone turns to when they're stuck.
Figure out AI workflows that 10x your output. Share easier workflows with colleagues. Become the go-to AI implementation person on your team.
I know people in supposedly forward-thinking, tech-focused organizations who still can't figure out how to use Notion. It's mind-boggling, but it happens.
If you can be that person, two things happen:
- You may become more useful to the team - that does not guarantee job security
- You build transferable skills - reputation and skills that work whether you stay or leave
The Framework: Four Questions to Assess Yourself
Take the AI Positioning Audit:
Question 1: Am I using AI just as a tool, or is AI core to how I think about building?
This applies whether you're a software engineer, business owner, or employee.
Question 2: Can I reclaim 20-30% of my work time minimum using AI?
Some tasks may not benefit enough from AI. Measure quality, review time and total cost before assuming that a 20–30% saving is feasible.
Question 3 (If employed): Am I becoming the AI expert in my organization?
If not, how can you make that happen?
Question 4 (If founder): Would my business operations collapse if AI tools disappeared tomorrow?
This is bold. ChatGPT, Claude, all of it - gone tomorrow. Does your business collapse?
If yes, you have a provider dependency to manage. That needs a recovery plan. Assign ownership and test a safe fallback.
I believed SimpleDirect had become highly dependent on AI. That was a dependency to manage, not proof that operational collapse is a desirable test of being AI-native.
Being able to keep operating during a provider outage can be a strength. Resilience does not show that a business uses too little AI.
Aim for useful automation with a tested recovery path, not operational collapse when a provider is unavailable.
Story 2: Distribution First, Product Second
A few episodes ago, I talked about why distribution is the only moat left in 2025.
This week, I got validation from a new breed of founders on Twitter. I analyzed their tweets, their startups, what they're building.
They're all talking about distribution first, product second.
They're building TikTok audiences, newsletter lists, and communities BEFORE they build products.
The logic is simple: Copying products is trivial now with AI. But audience moats aren't.
Build audience first. Validate with that audience second. Build product third for that audience.
Not build → validate → ship. That's the old way.
My Biggest Regret
I thought building distribution didn't matter for SimpleDirect Financing because I was targeting blue-collar customers.
I thought: "These customers use phones, call all the time, use pen and paper, Excel. Building a distribution moat won't work here."
I was wrong.
There are companies that built successful audiences using Facebook groups with exactly these customers. They post memes. The memes make blue-collar workers happy. It works.
I could've done this years ago. I could've started before launching my startup.
Instead, I focused on cold calls, BDB, distribution partners, business development. I never thought about building distribution first.
I was afraid: "I'm not blue-collar. How will they see me?"
But after digging into marketing the past few months, I realized it's just an excuse.
I'm good at talking about tools and resources. I could've opened a TikTok account talking about how home improvement contractors, roofers, HVAC people, garage workers can use technology to make their lives better and make more money.
That would've taken off. But I found excuses for years.
If I'd done this a few years ago on Instagram, YouTube, anywhere - I would've built a loyal blue-collar audience. Selling to them would've been way easier than cold calls and outbound.
The Inbound vs Outbound Reality
Always think about inbound, especially in B2B. Outbound costs a lot of money and doesn't work well anymore.
The cold messages I was seeing did not persuade me. That experience does not establish that outbound sales never work.
As an AI-minded, budget-conscious founder, it makes way more sense to do marketing first. Once you have a solid moat and enough money, maybe consider enterprise sales.
And you're still the best salesperson initially. I've tried hiring sales people multiple times. It's not worth it early on.
Your Distribution-First Action Plan
1. Start on day minus 100, not day one.
If you're figuring out distribution on day one, you're late.
Starting early can make room to test a channel and learn about demand. The 100-day schedule does not guarantee 5,000–10,000 followers, trust or customers.
2. Pick your platform and commit.
Post 3 times per week for 90 days minimum on the problem space your product will solve.
For e-commerce: Instagram/TikTok/YouTube Shorts
For tech products: Twitter/LinkedIn/Newsletters
Don't talk too much about yourself. Talk about the problem space. Engage people in that space.
3. Identify 3-5 distribution partners.
Remember ConvertKit? They became successful leveraging a huge affiliate marketer who had their target audience (creators). They paid affiliate percentages on every sale.
That was their initial moat.
4. Test demand with a landing page.
This isn't hard anymore. No Webflow, no Lovable needed. You don't need to write a single line of code.
Five years ago, I built my landing page from scratch with HTML, CSS, JavaScript. If I could do that then, you can do it now with no-code tools in 1-2 days.
Send that landing page to potential customers. Ask if they resonate with the problem. Ask if they want you to solve it.
Story 3: The ChatGPT App Store Could Be Your 2008 Moment
OpenAI announced apps and the Apps SDK preview on October 6, 2025. Review submissions and the app directory followed on December 17, 2025; the quoted platform audience did not guarantee usage of any individual app.
They're working with Booking.com, Expedia, Figma, Coursera, Zillow, Canva. Uber and Lyft coming soon.
They launched an App SDK Preview for developers. Sam Altman says it's "a new generation of apps - interactive, adaptive, personalized."
I've personally tried the Spotify plugin. It's not perfect, but it works. It built me a playlist. Got stuck a few times. It's raw.
That's where the opportunity is.
Why This Matters: Platform Moments in History
Apple example: The original company comparison did not establish individual launch dates, day-one participation or the causes of success.
TikTok example: The original launch-date and instant-millionaire claims were not sourced here. They do not establish reliable first-mover distribution or income.
If you start TikTok today? It takes significantly more time to get to a million followers.
Shopify example: The original Shopify date and category-leader claims were not sourced here; they do not establish guaranteed first-mover distribution.
Now: ChatGPT apps were a platform opportunity I was considering. A quoted platform audience does not mean an individual app receives distribution to every user.
That's the population of a continent.
Should You Build on ChatGPT's Platform?
Two sides to this:
The "Yes, Build Early" Case:
- Discovery may be possible; reach, acceptance and conversion are not guaranteed
- Users are forgiving in early days (Shopify apps didn't work perfectly last week when I tried)
- First movers might dominate categories (like Shopify apps that are still #1 today)
- If you launch in 6 months, you might be one of 10,000 apps fighting for attention
The "No, Stay Focused" Case:
- If you already have profitable products, distribution channels, moats
- Don't take dev time away from your roadmap just to build for ChatGPT
- Usage might be lower than you think (people use ChatGPT, but not necessarily the apps yet)
My framework for deciding:
Build if:
- Your existing users could benefit from using ChatGPT
- You could benefit from customers discovering your product in ChatGPT's early days
- You can test a bounded launch within your available time; 2–4 weeks was an illustrative sprint, not a deadline after which the opportunity disappears
- There's no category leader in your space on that platform yet
If three of those are yes, it's worth a sprint.
If not, stay focused.
Even If You Don't Build an App
Think about how to optimize your website/blog to be captured more by AI agents.
My website got captured 60-100 times last week by AI agents in China (3-second sessions, clearly bots). But ChatGPT hasn't captured it yet.
AI referrals may be worth measuring alongside other channels. This account does not establish low-maintenance traffic, conversion or an increase in business value.
Just don't chase it because everyone else is doing it. That's FOMO. Instead ask: "How can this benefit my business?"
How the Three Stories Connect
Story 1: AI is widening the performance gap
Story 2: Distribution is becoming the only moat
Story 3: New platforms create new opportunities with good timing
We're in a moment where AI made building easier, so products are commoditized. But distribution is still hard.
Audiences and channels are the new moat. New platforms are resetting distribution and creating opportunities.
I thought those choices might help my own business. They do not guarantee that a particular team will outperform other approaches.
The size and duration of any advantage would need actual follow-up evidence.
Your Action Plan This Week
1. Audit your AI use (take the 4-question test above)
2. Check out the ChatGPT App Store - see if it's worth your time
3. If employed: Evaluate relevant AI tasks, measure accepted output and total review time, and respect employer and data obligations before making room for other work
4. Start building distribution: Post 3x per week on your platform, talk about the problem space
5. Most importantly: Decide which type of builder you want to be
My eighteen-month permanence claim was speculative. Evaluate the actual tasks and results relevant to you rather than treating it as a universal deadline.
This article does not establish a twelve-to-eighteen-month point after which improvement becomes impossible.
Which type of builder are you? Take the 4-question AI positioning audit and email me at [email protected] with your results. I'm curious how many founders realize they're Type 2 when they think they're Type 3.
Get my free ebooks on consulting-first approach and de-risking your startup at founderreality.com
The Monday/Wednesday/Friday release schedule was an announcement at publication, not a current cadence guarantee. The permanent-gap thesis above remains an unverified prediction.
Daily thoughts: @TheGeorgePu on Twitter/X