Anton Braverman · production AI & governance
Getting an AI agent into production is the easy part. Keeping it governed is the work.
I’m Anton Braverman. I work on taking AI agents to production and holding them to what the business intended: gateways, guardrails, observability, and evaluation. This is where I write about what actually breaks, and how the controls get built.
- AI gateways
- Guardrails & content safety
- Observability
- Evaluation
- Organizational alignment
Selected writing
Recent essays
- Thesis6 min
The alignment problem most companies have is organizational
Model alignment is the labs' job. The version that breaks production is an organization that never decided what its AI was for.
- Thesis5 min
Why every AI sales call leaves the room more confused
The vocabulary grows every quarter while understanding shrinks. For a CEO or CTO trying to underwrite a decision, the bottleneck is not capability. It is clarity.
- Technical9 min
Every AI platform converges on a control plane. Build it on purpose.
Multi-team LLM traffic creates nine predictable problems that all want to live in one place. Whether that place is a single gateway, several gateways feeding a shared plane, or a runtime layer is an open question. The decision to design it is not.
- Technical10 min
Centralized guardrails across three clouds, and the cost of a new vendor
Each cloud's native safety tool solves a different slice. Putting guardrails in one place means a separate product, and that is a procurement and trust decision as much as a technical one.
Most of my hands-on work is enterprise AI agents going to production across AWS, Azure, and GCP. The quickest way to reach me is LinkedIn.
LinkedIn ↗