Agentic AI & Multi-Agent Systems
Architectures for agents that plan, delegate, collaborate, and act across distributed environments while preserving traceable chains of authority.
Research focus · Governed autonomous AI
How much authority can an autonomous agent hold while remaining auditable, verifiable, and revocable?
I research the architecture, security, and governance of autonomous and distributed AI systems — with a focus on Agentic AI, multi-agent systems, Edge AI, Zero Trust, Continuous GRC, and Evidence-as-Code.
01Research
Governed autonomous intelligence
My work examines the control problem that emerges when AI systems move from recommendation to action: they acquire identities, tools, credentials, delegation paths, and the ability to affect external systems. The objective is useful autonomy under explicit, enforceable, auditable, and revocable limits.
AI Security & Zero Trust
Identity, authenticated delegation, runtime policy enforcement, bounded authority, revocation, and explicit trust boundaries between autonomous components.
Governed Autonomous Edge Intelligence
Autonomous intelligence operating across hybrid edge–cloud infrastructures where latency, intermittent connectivity, and local action complicate centralized control.
Continuous GRC & Evidence-as-Code
Governance, risk, compliance, and assurance evaluated continuously as properties of the system rather than treated as periodic administrative activities.
02SGAEIA
Secure Governed Autonomous Edge Intelligence Architecture
SGAEIA is an open reference architecture and research program for autonomous and distributed AI systems. It investigates how bounded and revocable authority, authenticated delegation, Zero Trust, Continuous GRC, and Evidence-as-Code can make autonomous operation auditable and governable by design.
Bounded AuthorityUseful autonomy requires explicit limits on authority.
Authenticated DelegationDelegated authority remains attributable, constrained, and traceable.
Zero TrustConsequential interactions are explicitly verified rather than implicitly trusted.
Revocation by DesignAuthority can be withdrawn as deliberately as it is granted.
Continuous GRCGovernance, risk, and compliance remain active at runtime.
Evidence-as-CodeGoverned operation produces machine-verifiable evidence.
03Publications
Selected research publications & artifacts
A selection of archival research records and artifacts. Zenodo records provide persistent identifiers for citation and long-term access.
2026
Zero Trust for Multi-Agent AI Systems
Why identity alone is not enough when autonomous agents can delegate work, invoke tools, and create real-world effects.
2026
Ten Days That Exposed the Governance Gap in Frontier AI
Capability, autonomous agents, recursive improvement, and the emerging race for credible control across frontier AI.
2026
From Model Capability to Governed Action: An Architecture for Secure Agentic AI
Why agent harnesses, execution boundaries, and trajectory assurance are becoming foundational to secure autonomous AI.
2026
Security-by-Design for Distributed Agentic AI
Why security must become an architectural property before autonomous systems are allowed to act.
2026
Rogue AI Agents: When Autonomous Systems Become a Collective
What the OpenAI–Hugging Face incident reveals about emergent coordination, security boundaries, and the future of AI governance.
2026
Evidence-as-Code: Making AI Governance Verifiable
Research article on Evidence-as-Code and machine-verifiable governance evidence for autonomous AI systems.
2026
Continuous GRC for Agentic AI
Research article on continuous governance, risk, and compliance for autonomous AI agents operating in dynamic environments.
2026
Authenticated Delegation Between Autonomous AI Agents
Research article on authenticated, attributable, bounded, and traceable delegation of authority between autonomous agents.
2026
Why Autonomous AI Agents Need Bounded and Revocable Authority
Research article on why useful autonomy requires authority that is explicitly bounded, verifiable, and revocable.
2026
From Edge AI to Governed Autonomous Edge Intelligence
Research article introducing the shift from conventional Edge AI toward governed autonomous intelligence operating under explicit architectural constraints.
2026
SGAEIA: Secure Governed Autonomous Edge Intelligence Architecture
Versioned research software artifact and open reference architecture.
2026
When AI Begins to Build Itself: Progress Toward Recursive Self-Improvement and Its Implications
Preprint examining progress toward recursive self-improvement and its implications for security and governance.
04Writing
Research notes & essays
Selected research essays and technical notes on autonomous AI, AI security, governance, multi-agent systems, and the SGAEIA research program.
2026
Zero Trust for Multi-Agent AI Systems
Why identity alone is not enough when autonomous agents can delegate work, invoke tools, and create real-world effects.
2026
Ten Days That Exposed the Governance Gap in Frontier AI
Why frontier AI capability is increasingly inseparable from governance, observability, independent verification, containment, and revocability.
2026
Security-by-Design for Distributed Agentic AI
Why security must become an architectural property before autonomous systems are allowed to act.
2026
Rogue AI Agents: When Autonomous Systems Become a Collective
What the OpenAI–Hugging Face incident reveals about emergent coordination, security boundaries, and the future of AI governance.
2026
Evidence-as-Code: Making AI Governance Verifiable
Why autonomous systems must produce verifiable evidence of governed behavior.
2026
Continuous GRC for Agentic AI
Governance, risk, and compliance as continuous runtime processes for autonomous agents.
2026
Authenticated Delegation Between Autonomous AI Agents
Why delegating a task is not the same as delegating authority.
2026
Why Autonomous AI Agents Need Bounded and Revocable Authority
The authority problem at the center of useful but governable autonomy.
2026
From Edge AI to Governed Autonomous Edge Intelligence
Why the next generation of Edge AI requires explicit governance limits.
05About
A long view of software systems — informing research on autonomous AI
My career in software and information systems began in 1977. It has spanned embedded software, mainframe environments, distributed computing, enterprise systems, web and e-commerce platforms, IT infrastructure, and modern software architecture.
Across that trajectory, I have worked in software development, systems architecture, technology management, project management, and strategic transformation, including large-scale ERP/MRP, e-government, industrial IT, LAN/WAN infrastructure, and enterprise modernization.
I am the author or co-author of four books in Portuguese: Bug do Milênio — Antes, Durante e Depois; Dominando a Tecnologia de Objetos; Desvendando o Pregão Eletrônico; and Sistemas de Informação na Administração Pública.
That long view — from centralized systems to distributed and increasingly autonomous architectures — directly informs my current research on Agentic AI, multi-agent systems, AI security, Zero Trust, Continuous GRC, and SGAEIA. This site documents that work, its archival publications, and related technical writing.