PRODUCT CASE STUDY
Agentic Systems — LangGraph
Agent workflows combining specialist tools, persistent context, permission controls and observable execution.
- Role
- Product and technical lead — specialist agents and execution boundaries
- For
- Engineers exploring specialist-agent workflows
The user problem
One agent with every tool is difficult to reason about. Multi-step tasks need relevant capabilities and a way to preserve context, inspect execution and limit actions.
Product decisions
Use specialist roles under a supervisor rather than exposing every tool to every task. Separate research, code, knowledge and operations responsibilities. Treat operations permissions as a product boundary, with an explicit enablement step.
Engineering trade-offs
The documented implementation uses LangGraph orchestration, a capability registry, PostgreSQL/pgvector for persistence and retrieval, and AWS Bedrock models. Streaming and voice entry points are separate from the supervisor logic.
What exists today
Public writing documents the implemented architecture. The repository is private and there is no public demo.
Evidence & next steps
Implementation evidence is separate from measured user or business outcomes. Next: validate the complete user journey and its results.