How We Frame Machines

Investor Due Diligence Report

substackEducation

An educator and journalist examining how we frame our relationship with AI. I write about the mental models and metaphors that shape AI use in education, work, and creativity—because how we conceptualize these systems determines what we do with them.

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Key Metrics

Subscribers

300 paid

Verified

Weekly Growth

N/A

Revenue Analysis

Pricing

$5/mo

$50/yr annual option

Est. Monthly Revenue

$1K

300 paid subs

$1K/mo – $1K/mo(±0%)

Engagement

Avg Comments/Post

1.0

Avg Likes/Post

19.0

Engagement Rate

0.67%

(comments + likes) / subscribers

Quality & Publishing

Audience Quality Score

74Good

0100

Publishing Pace

Previously Weekly

0.8 posts/week

Score based on available components only.

Component	Score	Weight

Competitive Landscape (Education)

Newsletter	Subscribers	Weekly Growth	Price	Platform
AlgoMaster Newsletter	141K	+0.4%	$29/mo	substack
Uncharted Territories	124K	+0.4%	$10/mo	substack
All About Psychology	104K	+1.1%	$5/mo	substack
The Shit No One Tells You About Writing	84K	N/A	$10/mo	substack

Revenue Trajectory

Estimated monthly revenue over time

Month	Subscribers	Est. Revenue	Change
Feb 2026	3K	$1,192.5	—
Mar 2026	3K	$1,192.5	~0%

Risk Assessment

Key risk factors for due diligence

High

Platform Dependency

Hosted on substack subdomain

Medium

Key Person

Single-author publication — key-person dependency

Low

Revenue Model

Active paid subscription tier

Monetization Readiness

Monetization status

Subscriber threshold

3K subscribers — above the 1K category median for first paid tier

Has paid tier

Active paid subscription offering

Peer monetization

100% of 97 similar-size peers in Education have paid tiers

Pricing position

$5/mo vs $5/mo category median (493 newsletters)

Pricing History

Date	Monthly	Annual
Mar 2026	$5	$50

Data Quality

Report Data QualityFull - All metrics available

Subscriber Confidenceverified

Disclaimer: This report is generated automatically based on publicly available data and proprietary estimation models. Estimated subscriber counts are derived from engagement patterns and should be verified through direct disclosure. Revenue estimates are based on known pricing and estimated paid subscriber counts. This report is for informational purposes only and should not be the sole basis for investment decisions.