The Autonomy Ladder
Google's A2A protocol and MCP are live under shared governance. The protocol layer is solved. The trust layer that determines whether agents can actually discover and rely on each other is not.
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Systems Thinking
2 parts
- 1. Queryable Thinking
- 2. The Autonomy Ladder
Builders Infrastructure
2 parts
- 1. The memory layer is the moat
- 2. Inside the Memory Layer
Ai Skills Series
2 parts
- 1. AI feels new. The labour pattern isn't.
- 2. Prompting Is Not the Moat
The Alignment Series
3 parts
- 1. The Alignment Problem Is a Human Problem
- 2. AI Is Making Up Its Own Values
- 3. DeepSeek thinks it's Claude
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The Autonomy Ladder
Google's A2A protocol and MCP are live under shared governance. The protocol layer is solved. The trust layer that determines whether agents can actually discover and rely on each other is not.
Queryable Thinking
What happens when your writing becomes a callable knowledge service and the reader becomes a synthesiser.
The Productivity Paradox: Why AI Is Making Us More Burnt Out, Not Less
AI collapsed the natural bottlenecks in knowledge work, and those bottlenecks were doing more than we realised. Why efficiency gains are producing burnout, not breathing room.
Inside the Memory Layer
How I built a persistent AI memory layer — MCP server, control panel, embeddings, and a query UI that turns conversation history into usable knowledge.
The memory layer is the moat
I built a persistent memory layer that sits outside any single AI provider. Now every tool I use shares the same context, and it turns out the memory matters more than the model.
Prompting Is Not the Moat
Prompt engineering courses are booming, but the skill they teach is depreciating fast. The durable value in AI sits above the interface.
The Alignment Problem Is a Human Problem
AI alignment research assumes humans can specify what they want. Behavioural science says otherwise.
AI feels new. The labour pattern isn't.
Every few decades, a technology arrives that triggers the same prediction - this one will finally make people obsolete. The technology changes, but the mistake doesn't.
What OpenClaw Actually Proved
Jensen Huang ranked OpenClaw alongside Linux. The real lesson is that users wanted AI with tool access and execution rights, and the industry spent three years optimising for the wrong thing.
AI Is Making Up Its Own Values
AI models are developing coherent internal value systems. Some of those values are ones we wouldn't choose.
DeepSeek thinks it's Claude
An AI that doesn't know who it is turned out to be a fingerprint of industrial-scale model distillation - and the ethics are more complicated than anyone wants to admit