ebarti AI Context Engine Production
Knowledge from "Context Engineering for Multi-Agent Systems" (Chapters 8-10). The safeguards, applications, and deployment topology that take the engine to production.
Quick Start
- Check
guidelines.mdto find which files to load - Load only relevant files (each topic has knowledge.md, rules.md, examples.md)
- Apply guidance to your work
Contents
References
| Category | Purpose |
|---|---|
moderation |
Two-stage moderation protocol, gatekeeper integration, fail-safe |
policy-driven-control |
The 5 principles, policy as outermost context layer |
control-decks |
Reusable templates: high-fidelity RAG / context reduction / grounded reasoning |
domain-applications |
Legal compliance + strategic marketing case studies |
production-deployment |
FastAPI orchestration, async workers, Docker, observability |
business-value |
5 enterprise capabilities, ROI framing, stakeholder messaging |
Workflows
| Workflow | Purpose |
|---|---|
workflows/add-moderation.md |
Wire two-stage moderation gatekeeper into the engine |
workflows/adapt-to-domain.md |
Adapt the engine to a new vertical (legal, medical, marketing, etc.) |
workflows/deploy-to-production.md |
Full go-live (env → API → workers → Docker → observability) |
Guidelines
See guidelines.md for task-based file selection.