# Useful agents need boundaries.

Adrien Murillo — Murillo Consulting

What public demonstrators allow us to explore: control data, side effects and traces before extending autonomy.

## Separate answers from actions

Producing text and changing a system carry different constraints. Once an agent can call tools, its permitted actions, accessible data and requirements for human approval must be defined. This work comes before multiplying integrations: a polished interface does not make side effects less real.

## Make the boundary visible

Gate explores a local gateway between AI clients and providers. Its documented scope includes data protection, policies, budgets, fallback and signed traces. The architectural benefit is placing controls at an explicit boundary. A gateway cannot, by itself, understand all the business context of a call or guarantee answer quality.

## Prepare for interrupted work

An interrupted action can leave a system in a partial state. The LangGraph Resilient Agent demonstrator explores policies, human approval and auditing side effects. An operational design should specify what can be replayed, what must be checked and what needs intervention. A log helps reconstruct a sequence. It does not automatically repair it.

## Keep the scope clear

These projects are public experiments. They show architecture choices and testable mechanisms, without claiming professional AI engagements. Examples need review of secrets, access, data retention and operations before real use. An AI security engagement is scoped around your use case, the controls to test and the skills required.

## Sources
- [Gate — code et documentation](https://github.com/murillo-consulting/Gate)
- [LangGraph Resilient Agent — code et documentation](https://github.com/murillo-consulting/langgraph-resilient-agent)

## Navigation
- [Independent engineer and trainer.](/en/profil)
- [Engineering services.](/en/services)
- [Selected work.](/en/realisations)
- [Open-source projects.](/en/projets)
- [Guides to put into practice.](/en/ressources)
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- [From scope to handover.](/en/approche)
- [Real contexts. Real constraints.](/en/secteurs)
- [Learn by making decisions.](/en/lab)
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