AI AGENT ARCHITECTURE
32 agents, 249 patterns from 2,132 signals (Runwell Systems, 2024-present)
AI agent architecture is the design and deployment of autonomous systems that handle business workflows end-to-end. Instead of one monolithic AI, you build a team of specialized agents, each with defined tools, rules, and context boundaries.
WHAT I BUILD
- Multi-agent orchestration with role-based delegation
- Token budgets and context window management
- Graduated autonomy (supervised to autonomous operation)
- Self-improving learning loops (signals to patterns pipeline)
- Cross-project pattern detection and proposal systems
- Agent-of-agents hierarchies (47+ orchestrated pipelines)
HOW IT WORKS
- Define agents with scoped tools, rules, and context limits
- Route tasks to the right agent based on project and domain
- Capture every commit, bug fix, and decision as a learning signal
- Synthesize signals into reusable patterns daily
- Promote agents from supervised to autonomous based on track record
RESULTS
- 32
- autonomous agents deployed across 11 client products
- 249
- behavioral patterns extracted from 2,132 learning signals
- 47+
- orchestrated pipelines running daily across all projects