Public dossierAI in productionAgentsFrontier

Simone Bova / AI engineer, founder, production

The model is a commodity. The method isn't.

I build AI systems that hold up in production. Founder & CTO of Yempik (si apre in una nuova scheda), AI engineer at Intarget, maintainer of code-os. I sit in the room where decisions get made and in the repo where things ship.

This is my public archive: systems built, method, what I think about the AI frontier. No slides. Just work you can inspect up close.

FounderEngineerWriting in public

Public dossier / Version 0.2
Shipped before it was perfect

Operating doctrine, not theory

Method

01

Model ≠ Problem

If the agent fails, the flaw is in the design. Models have been more than good enough for a while.

04

"Ignorant" AI-native redesign

Redesign the process from zero under one constraint: one person + these tools. An org chart is not a workflow.

05

The expert's signature, not the token lottery

Predictable quality via tests on real scenarios and pass^k. The expert's standard lives in the system.

06

The harness is the asset, the model isn't

Tools, contracts, evals, observability: yours. The model is a swappable component.

OWN THE HARNESS, SWAP THE MODEL.All 8 principles →

Altitude, snow, safety margin

Fuoripista

The mountain punishes the same mistake production does: trusting yesterday's conditions.

Winters on snow, summers on rock. Off-piste skiing and high-altitude hikes are the part of my life where risk assessment isn't a slide: bulletin, checks, margin. Then you drop in, and the fun is real.

They stay here as side notes: present enough to be true, never big enough to become a costume. There's also a story with a helicopter, one night, and a thinner margin than I like to admit. Another time.

Terrain of choiceFresh powder
Before the drop-inBulletin + checks
Rule no.1Margin

Contact

If the problem is real and needs to reach production, let's talk.