Service 03
Agent Systems & Autonomous Operations
Single AI agents are useful. Fleets of coordinated agents are transformative. I design multi-agent systems where AI agents coordinate, learn from each other, and measurably improve over time.
Fleet orchestration handles the coordination: which agent works on what, how they share context, and how conflicts are resolved. Reliability engineering keeps them running: liveness monitoring, health checks, and automatic recovery from failures.
The key innovation is scored improvement loops. Every agent cycle produces measurable quality metrics. If quality improves, the change is promoted. If it degrades, it's rolled back. This turns manual workflows into self-improving pipelines with verifiable quality gates.
- Agent fleet design with orchestration topology
- Quality gates & improvement loop architecture
- Monitoring, observability & liveness instrumentation
- Prototype-to-production handoff plan
Teams automating complex workflows, companies building AI-native operations, and engineering leaders designing autonomous systems.