The Input Age — Launch of the Public Intelligence System
January 19, 2026
“Everyone is becoming a creator. Almost no one is becoming a better thinker.”
Why intelligence—not output—is the real scarcity
For the last few years, the dominant narrative was about creation:
- become a creator
- build an audience
- ship more content
- scale output
AI completed that arc. Output is now frictionless. A single individual can generate:
- 10 blog posts before breakfast
- a pitch deck in 5 minutes
- a market map in one prompt
- a full report in an afternoon
When something becomes cheap, it stops being valuable.
The real shift: from output to input
As output becomes abundant, the constraint moves. The shift isn’t new—it’s economic gravity.
The constraint has moved inside the individual:
- From: “Can you produce?”
- To: “Can you think clearly enough to ask the right questions?”
We’ve entered the Input Age. Intelligence is no longer measured by how much you produce, but by the quality of what you feed into the system.
Proof, not philosophy
This isn’t a vibe. There’s data behind it. Anthropic’s Economic Index shows a clear correlation between output quality and the sophistication of the prompter.
Not access. Not tools. Not tokens.
Skill. Judgment. Mental models. Domain depth.
A shallow mind gets shallow output. A PhD-level output requires PhD-level input. AI doesn’t democratize intelligence—it amplifies it.
Why “better consumers” matter more than creators
At the end of 2025, I began a series called “How to Become a Better Consumer in 2026.”
It was contrarian on purpose. Everyone was teaching people how to create with AI. Almost no one was teaching people how to:
- read better
- filter better
- ask better questions
- allocate attention more intelligently
When output is infinite, consumption becomes the leverage point. Your outcomes are downstream of what you consume—and how critically you consume it.
The intelligence gap across EdTech, FinTech, and HealthTech
EdTech is one of the most important industries in the world:
- it shapes how people learn
- how they reskill
- how they access opportunity
- how nations build human capital
Yet if you try to understand it clearly, you hit the same problems:
- everything is called “EdTech”
- K‑12 tutoring is compared to enterprise SaaS
- MOOCs are analyzed alongside OPMs
- consumer apps and government platforms are lumped together
Metrics are vague, incentives unclear, accountability missing.
The same pattern shows up in FinTech and HealthTech. Most analysis falls into one of three buckets:
- Marketing masquerading as insight
- Investor decks without operational depth
- Academic work that never touches reality
What’s missing is structured, decision‑grade intelligence across all three verticals.
Skin in the game changes everything
Most EdTech analysis is written by people who don’t live with the consequences. I do.
EdTech is not a side interest. It’s one of the three industries I’m betting my time, reputation, and company on—alongside FinTech and HealthTech.
At Growth Flow Engineering, we work with EdTech companies to:
- design growth systems
- improve distribution efficiency
- make better build vs buy decisions
- navigate AI disruption without hype
This research isn’t neutral commentary. It’s operational intelligence. If it’s wrong, we pay for it—in client outcomes, strategy, and credibility.
Our north star: beating McKinsey by being built for now
We want to be better, faster, and more cost‑efficient than legacy consulting firms.
Not louder. Not prettier. Not buzzier.
We optimize for:
- Speed to insight — time from question to clarity
- Cost per output — intelligence density per dollar
- Knowledge per minute — value per unit of attention
- AI leverage — we spend $10\times$ more time than you do, using machines intelligently on your behalf
If you spend 8–10 minutes reading something we publish, we want to have spent 1.5 hours thinking, validating, prompting, cross‑checking, and structuring it.
Your attention is the most expensive input in the system. We treat it that way.
What we’re building
We’re building the Public Intelligence System across EdTech, FinTech, and HealthTech — starting with EdTech.
Not a newsletter. Not a content series. Not hot takes.
A knowledge system.
We’ve broken EdTech into 10 clean, non‑overlapping segments, each with its own:
- economics
- buyers
- incentives
- regulatory constraints
- AI exposure
- failure modes
The 10 segments
- K‑12 Institutional Platforms
- K‑12 Supplementary Learning
- Higher Education Degrees (Online & Hybrid)
- Test Prep & Professional Certifications
- Alternative Credentials & Skills Signaling
- Corporate L&D & Upskilling
- EduFin (Education Finance Infrastructure)
- Interactive & Emerging Delivery Models
- Assessment, Integrity & Learning Analytics
- Institutional Operations & Admissions
Each segment will follow a repeatable, rigorous framework:
- scope and boundaries
- value chain mapping
- key players and power centers
- unit economics and metrics that matter
- regulatory and policy forces
- AI impact (incremental → structural → destructive)
- capital stack incentives
- predictions with falsifiability
This is wiki‑style research: modular, updatable, referenceable, and designed for reuse in real decisions.
Why this exists (and why you might follow it)
I asked myself a simple question:
“If someone else were curating this level of insight — would I follow them?”
Only if:
- they had skin in the game
- they showed their work
- they respected my time
- they weren’t optimizing for engagement
- they weren’t afraid to be wrong publicly
That’s the standard we’re holding ourselves to.
This is for:
- CXOs making platform and partnership decisions
- Founders searching for real white space, not vibes
- Investors who want depth without McKinsey invoices
- Operators who need to understand second‑order effects
- Policy thinkers who want to see how incentives really work
The deeper bet
In a world of infinite output, trusted input curators become the new institutions.
Not media companies. Not influencers. Not loud creators.
Institutions built on:
- judgment
- consistency
- accountability
- taste
- skin in the game
We’re building that institution—one segment at a time, in public, with sources, with structure, and with consequences.
What comes next
- EdTech deep‑dives (10 segments now complete)
- FinTech and HealthTech system builds
- structured decision tools and datasets
- a living wiki anyone can navigate
- contributor pathways for real operators
- open debate, not dogma
This will evolve. It will get sharper. And yes—it will sometimes be wrong. But it will always be honest, structured, and useful.
Final thought
AI didn’t make thinking obsolete. It made thinking visible. Your inputs are now legible. Your questions are amplified. Your depth—or lack of it—shows up in the output.
Welcome to the Input Age. We’re building the intelligence stack we always wanted. You’re invited to tag along, debate, and share with deep thinkers.
Value per unit of attention is the North Star metric for this series.
— Moses Sam Paul, Growth Flow Engineering
About the Author / Methodology
Moses Sam Paul builds growth systems for EdTech companies at Growth Flow Engineering. This series is produced with a decision‑grade intelligence workflow: defined scopes, source‑first research, cross‑validation, and structured outputs optimized for executive action.
Learn more about the author: https://theinternetofvalue.xyz/author