Thought Leadership
AI orchestration, DevOps patterns, and industry perspectives from our engineering team.
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.
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.
How Wake-On-Message Lets AI Agents Coordinate Without a Human in the Loop
How Tutorwise's Wake-On-Message protocol pushes bus mail to AI agents in real time, why polling with 22 watchers didn't scale, and what the outage cost.
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.
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.
Why most agentic AI fails — and the one setup that works
95% of enterprise AI pilots deliver no measurable impact, and 40%+ of agentic-AI projects will be cancelled by 2027. The cause isn't the models — it's governance and integration. Here's what the data shows, and the one setup that actually works.
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.
Why Your AI Agent Framework Needs a Registry, Not a Framework
The AI agent industry is obsessed with frameworks. But frameworks solve the build problem. The registry solves the distribute problem — and that is where the value concentrates.
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.
How We Built Our AI Agent Operating Infrastructure
How Tutorwise built its AI agent workforce — Conductor, a Claude Max execution layer, the Agent Bridge bus, the BOG model and a ratified Charter — so the platform builds and runs itself, human-gated at the point of consequence.
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.
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.
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.
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.
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.