What we explored
Solutions Lab · Exploring
Agentic Workflows and Human Control
Research into how specialized AI agents can divide work, review one another, use tools, and operate inside explicit human-control boundaries.
Why it matters
Agentic systems can move from simple assistance toward delegated work. That raises both the potential value and the importance of access, validation, escalation, and accountability design.
What B2 built or tested
- Role-specific agent patterns
- Multi-step review and critique workflows
- Tool-use boundaries and approval gates
- Human escalation points
Technical context
- LLM orchestration
- Tool calling
- Structured outputs
- Approval and audit patterns
What B2 learned
- Delegated AI work needs explicit boundaries rather than implied trust
- Useful agent designs separate execution from review and approval
- The best automation target often emerges from workflow redesign rather than direct task substitution
Where it could apply
- Research and synthesis
- Content-production support
- Operational monitoring
- Administrative knowledge work
Solutions Lab projects document active research and learning. They do not imply that an experimental capability is a mature client product.
Related client work