//00 agentic ai lab · portugal
AI agents in production,
built, observed and attacked
with evidence.
AI agents in production: how they are built, operated, evaluated, governed and attacked, tested on a real stack. Flagship area: AI Ops Sec, agent security and observability.
Lab areas
7AI Ops Sec
Agent security and observability
Agents and orchestration
How to build an agent that survives production
Automation and ROI
Business processes handed to agents, with the numbers
Evaluation and quality
Knowing whether the agent got it right before the client does
Governance and regulation
What the law already asks of agents, read by an operator
Models and infrastructure
Local and commercial models, and the infrastructure that serves them
Tokenization
The token as the economic unit of AI: what it costs, what it saves, what it hides
Latest articles
06- Agents and orchestration
Multi-agent workflows in production: who is actually running thousands of agents (and who is pretending)
49 independent publications in three days say everyone wants multi-agent. The real question: when does it work, and how much does the supervisor cost that nobody measures.
- AI Ops Sec
OWASP Agentic Top 10 mapped to a real stack: what each ASI demands from those who run agents
I took the ten OWASP risks for agentic applications and mapped each one to a concrete piece of a production stack. The table, the incidents, and the config that is missing.
- Evaluation and quality
Testing a model before trusting it
I measured a decision model across 1,202 documents for six cents. The result matters less than the method, and the method caught me publishing the wrong conclusion.
- 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.
How this site is built
- 01Code and articles live in a public repository. Every change lands through a reviewed pull request.
- 02No trackers, no cookies, no third-party scripts. Static HTML served from a CDN.
- 03Every article lists its sources and what changed after publication.
- 04Mistakes are fixed in public, in the history of the article itself.