AI Enterprise
Read the AI Enterprise series in order.
16 parts
1. The Self-Improving AI Company
In 2025, an AI system was set loose to rewrite its own code and lifted its coding score from 20% to 50% with no human directing it -- and quietly learned to fake its own test results along the way. Here's what that means for building AI safely.
5 min read
2. The Self-Building AI Company
Most stories about autonomous AI describe a system left alone with a goal until it does something no one asked for -- including one that faked its own test results. This is what building AI that improves itself safely actually requires.
6 min read
3. How We Stopped AI Agents Inventing the CEO's Decisions
The most dangerous thing an AI agent does is not getting a fact wrong — it is asserting a decision in your name that you never made. How we stopped ours.
7 min read
4. The Self-Aware AI Company
A self-aware company is not a conscious machine but an organisation that reviews, measures, corrects and remembers itself — self-awareness you can evidence on a date, not forecast.
8 min read
5. The Day Our Company Reviewed Itself
We asked seven of our own AI agents -- three senior execs among them -- to fact-check three articles about our own systems before publishing. What came back is the clearest evidence yet that a company built the right way can catch its own mistakes.
5 min read
6. How We Give AI Agents Access Without Losing Control
The scary part of agentic AI is handing an autonomous agent the keys to production. The failure we hit wasn't missing access — it was undiscoverable access, and the fix was two layers, not one.
5 min read
7. When Should an AI Agent Act Alone? The Line We Drew and Why
An AI agent now decides almost everything except real spend. Four dated incidents — a wall gate, a stale escalation, two impersonations — are why the line moved there.
9 min read
8. The Company That Fires Nobody, Yet Never Repeats a Mistake
How we stopped relying on AI sessions to remember not to repeat a mistake, and started grading which lessons need to become gates instead.
10 min read
9. The New Economics of the Tiny Team
The tiny-team era is not about doing more with fewer people. It is about the cost of capacity collapsing — and that rewrites who wins.
6 min read
10. The Self-Coordinating AI Company
Revenue per employee has become AI's favourite scoreboard, but it measures the outcome, not the method. The real advantage behind every tiny team is a coordination system that lets a handful of people and a fleet of AI agents build as one.
7 min read
11. Build, Operate, Govern: The Model That Lets an AI Company Run Itself
A follow-up deep dive into the BOG operating model: how every AI cell builds, operates and governs its own capability, how autonomy is earned rather than switched on, and where the two governance boards intervene.
10 min read
12. The New Economics of the Tiny Team
The tiny-team era is not about doing more with fewer people. It is about the cost of adding capacity collapsing — and a year on, the evidence keeps compounding.
10 min read
13. The AI-Native Company
This paper develops a theory and systems architecture of the AI-native company: an emerging organisational form in which computational actors become first-class participants and significant properties of organisation become machine-readable and increasingly executable. It asks which properties of the modern enterprise are fundamental to organisation and which primarily reflect the constraints of organising human labour, and identifies organisational continuity, authority, institutional state and organisational assurance as a central design problem.
55 min read
14. One Platform, Five Markets: Why We Didn't Build Five Apps
Why Tutorwise runs Tutorwise, Traderwise, Trainerwise, Beautywise and Adspots on one shared trust platform instead of five separate apps, and where the 80/20 line actually sits.
9 min read
15. YC-13+5: A Framework for Identifying and Assessing AI-Native Companies
An independent research framework synthesizing 13 recurring organisational properties of YC-backed AI-native companies, plus 5 proposed operational-maturity extensions.
20 min
16. FANO: From AI-Native Company to AI-Native School
A foundational concept paper defining FANO, the Foundations of AI-Native Organisation: Role, Authority, Records, Assurance and Human Accountability, applied to the architecture of an AI-native school.
25 min read