The four-axis ranking
We rank humanity’s most important problems on four quantifiable dimensions — quantity of humans affected, severity per capita, current solution quality, and addressable market size — and package each as a proposal in the spirit of Musk’s Hyperloop Alpha. This document is the proposal for pedagogy at scale. Every number below is sourced and tagged with confidence. Every ranking is a conjecture, open to refutation.
Quantity · humans affected
1.5B
highSeverity · WTP / wealth
20%
medCurrent solutions
3.0 / 10
medMarket size · TAM
$6.0T
highWhat we are trying to solve
Benjamin Bloom's 1984 research showed one-on-one tutoring raises student performance by 2 standard deviations versus classroom instruction. The problem was cost: one tutor per child is infeasible at population scale. AI tutoring changes the economics. 1.5B children are undereducated globally (UNESCO); billions more adults lack skills they could have acquired with better pedagogy. This is the problem Deutsch writes about most directly in The Beginning of Infinity, better explanations compound across generations.
The gap between the world and the world that is physically possible
Today: 1:1 human tutoring produces +2σ outcomes vs classroom (Bloom 1984) but is unaffordable for most. Median schooling under-delivers; global learning poverty ~70% in low-income countries.
Current solution quality is rated 3.0 / 10 (med confidence) — meaning there is substantial unclaimed ground between what exists and what is possible. estimated — 1:1 tutoring (+2σ per Bloom 1984) remains gold standard but unaffordable for most; LLM tutors emerging but unproven at scale.
Who is already working on this
5 entities are currently working on this problem across public markets, private companies, and research orgs. Each is evidence the market is real; none has obviously solved it.
Duolingo
public · USALanguage learning reaching 100M+ monthly users. Expanded into math, music, and literacy.
$14.5B
Replit
private · USABrowser-based coding platform. 100M+ learners worldwide; AI agent for app-building compresses learn-to-ship cycle.
$3.0B
Speak
private · USAAI conversational tutor for language learning, unlimited speaking practice at marginal cost.
$1.0B
Synthesis
private · USAAI tutor for kids (math, reading). Attempting to close the 2-sigma gap for ages 7-14.
undisclosed
If we solve this, here is the world we get
After · 10 years
Every learner has access to AI tutoring matching the best human tutors, in any language, at near-zero cost. Bloom 2-sigma becomes the default, not the exception.
Requests for startups · 2 concrete companies to build
The Bloom 2-sigma tutor
1:1 tutoring beats classroom instruction by two standard deviations and has been unaffordable for 4,000 years. Build the AI tutor that delivers it for the marginal cost of inference, in any language.
- why now
- Models crossed the threshold where they can diagnose a misconception and adapt — not just answer — at conversational latency and cost.
- shape
- A tutoring product (not a chatbot) with a real pedagogical model: mastery tracking, spaced retrieval, Socratic dialog, and outcome measurement against standardized gains.
- success
- A median student using it gains the Bloom 2-sigma effect, reproducibly, on independent assessments.
Credentialing that routes around the diploma
Employers want proof of skill; the degree is a $1.5T noisy proxy. Build the verifiable, adversarially-robust skills-assessment standard that employers actually trust.
- why now
- AI both threatens take-home assessment integrity and enables proctored, adaptive, cheating-resistant evaluation at scale.
- shape
- An assessment + credential issuer with employer-side validity studies, designed from day one to resist AI-assisted cheating and to be portable across employers.
- success
- A meaningful share of hiring uses the credential as a primary signal, decoupling opportunity from tuition.
full rubric + framing on the Requests for Startups page.
What the market can pay
The world is already paying $6.0T per year against this problem (global education spend (UNESCO Global Education Monitoring Report); EdTech slice ~$400B and growing; high confidence).
A successful solution does not need to capture more — it needs to redirect a meaningful slice of existing spend, plus the latent willingness-to-pay implied by the severity score above. The cost ceiling for a real solution is bounded by this number; everything cheaper is dominated, everything more expensive is a non-starter.
What could go wrong, and how we know we are not wrong
Section in progress
Failure modes, ethical considerations, and the conditions under which this whitepaper would be falsified are being authored as the weekly cadence ships. The Deutschian commitment: every claim above is a conjecture; we publish the conditions under which we would update. New whitepaper sections ship with each Monday newsletter drop. Subscribe to get the upgrade, or contribute on GitHub.
Who would back this
Capital allocators with a stated thesis or deployed portfolio in this domain. This is a starting list — Exa Websets enrichment will expand it to direct check-writers per company.
Emergent Ventures
Fast grants. High-variance, unconventional, talent-first.
O'Shaughnessy Fellowships
$100k for creators across domains, art, science, history, startups.
Rise Fund (TPG)
Growth-stage impact investing with rigorous Impact Multiple of Money scoring.
What the thinkers say
“Bad explanations waste billions of childhood hours. Good explanations compound across generations. Pedagogy is an epistemology problem.”
“Asks whether we can dramatically improve the quality and speed of learning. Cites tutoring and personalized instruction as high-leverage unsolved problems.”
“Education quality is the compounding lever. Progress requires transmitting knowledge at higher fidelity and lower cost to each successive generation.”
“Finding and developing talent is an underrated problem. Most selection is bad, most mentorship is worse, and the tails of ability are where civilizational value compounds.”
Where this is wrong, tell us
Every number on this page carries a source and a confidence tag. Every section open to refutation. If a citation is wrong, a number is stale, or a conjecture is unfounded — file a correction.
corrections → use the feedback widget in the nav · open issue at github.com/adamtpang/optimism.fun