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10- AI Ops Sec
J-Lens: reading what the agent thinks before it acts, and what that changes in observability
Anthropic showed an internal space where the model keeps what it has in mind. I ran the lens on four synthetic prompts against a 27B Qwen and designed the third lane of agent observability.
- AI Ops Sec
The danger is not the connector. It is what gets into the model, and what it can do next
'Is this MCP secure?' has an answer. The missing question is another: what did I just authorise into a model that can also act? Two attack chains, what is at stake, and observability over MCPs.
- Tokenization
The five thousand dollars you never see on the invoice: why cache is your hidden balance sheet
Your invoice shows what you spent. It never shows what you avoided spending. In my own operation, what I avoided was four and a half times what I paid, and it appears nowhere.
- Tokenization
The agentic multiplier: where your tokens REALLY go
In an agentic system, most of the tokens you pay for are never seen by anyone. It is called alpha, and in my own operation it reaches 11.1×. Here is how to measure it before the bill measures it for…
- Tokenization
The 35% you don't see: why "price unchanged" can be a disguised increase
The vendor announces "price unchanged". Your bill goes up 35%. How the tokenizer changes between versions and yields more tokens for the same text, and how to measure the factor in your operation.
- Tokenization
The 2026 Token Crunch: Why Your AI Bill Exploded (and How to Cut It 70–90%)
Per-token price fell from $10 to $2.50/M in a year. Bills multiplied because agents burn 5–30× more tokens. Five documented levers cut 70–90% of cost.
- Tokenization
5 Prices for One Token: What You're Actually Paying for Your AI
I pay €99/month for a subscription. Over the same period I consumed $565 in API-equivalent value. Five components, five prices, and why the aggregate lies.
- Tokenization
Tokenization culture: a working manifesto
Why the move to tokens is not just a technical shift but a cultural one, and what that means for the next decade of software.
- Agents and orchestration
Building multi-agent systems that don't collapse
Patterns and anti-patterns from shipping coordinator–worker agent loops in production.
- Tokenization
The prompt is the product
Treating the system prompt as a first-class artifact, versioned, tested, and owned by the team that ships it.