I design and operationalize agentic AI systems that scale beyond demos; systems that reason, collaborate, evolve, and operate safely in real enterprise environments.

My work sits at the intersection of cloud-native architecture, autonomous agents, and governance-first AI, with a focus on turning emerging capabilities into repeatable, trustworthy platforms.

Agentic AI architectures
Multi-agent systems, orchestration patterns, arbiter/supervisor models, and swarm-based workflows

Adaptive Intelligent Systems
Designing distributed AI systems as living systems capable of reflection, evolution, and controlled autonomy

Enterprise AI platforms
Moving from pilots to production through governance, observability, identity, and lifecycle design

Cloud-native & serverless AI
Event-driven, distributed systems built on AWS primitives

• Agent-to-agent coordination & capability discovery
• Event-driven orchestration and semantic routing
• Human-in-the-loop control surfaces
• Boundaries for autonomy (functional, decision, temporal, governance)
• Observability, trust, and auditability for autonomous systems

If you care about how AI behaves at scale, not just what models can do, we’re likely thinking about the same problems. You can read some of my work on Agentic AI here: https://aws.amazon.com/prescriptive-guidance/agentic-ai/

Agentic Swarm Architecture
A self-regulating, event-driven, multi-agent system with generative, evaluative, operational, and reflective agents

Arbiter & Supervisor Patterns
Control-plane architectures for coordinating autonomous agents without centralizing intelligence

Operationalizing Agentic AI
Turning autonomy into enterprise value through platforms, not prompts

Adaptive Governance Models
Governance as a living system — not static policy

• Cloud: Amazon Web Services
• AI & Agents: Amazon Bedrock (open and prapriatary models), Bedrock AgentCore, multi-agent frameworks (strands, lengraph), A2A protocols
• Compute: Lambda, ECS, EC2, AgentCore Runtime
• Eventing: Amazon EventBridge, Amazon SQS
• Data & State: DynamoDB, S3, AgentCore Memory, Amazon Aurora
• Observability: CloudWatch, Xray, OpenTelemetry
• IaC & CI/CD: CDK, CodePipeline

I regularly publish long-form pieces on:

• Agentic AI maturity
• Why autonomy without boundaries fails
• Human–AI decision systems
• Adaptive systems and complex architectures

You’ll find essays, reference architectures, and experimental code across my repos and socials

I enjoy collaborating with:

• Engineers building real multi-agent systems
• Architects tackling AI governance at scale
• Architechs and Engineers tackling complex problems at scale
• Researchers exploring CAS, autonomy, and adaptive control
• Teams trying to bridge the gap between model capability and operational reality

LinkedIn: in/aaron-sempf

Blog / Writing: Medium | Personal Blog | AWS Builder Community | AWS Blog

“The defining question isn’t what your AI can do;
it’s how safely and intelligently your system can evolve.”