Advisory
Architecture advisory for production AI systems.
Production AI Architecture Advisory
Bring in principal review before a rewrite, vendor choice, hiring plan, or architecture commitment becomes expensive to unwind.
The review draws on production patterns from ActiveWizards and Production-Ready AI Agents.
Start Here If
- A prototype is becoming customer-facing or operationally load-bearing.
- Your team is choosing orchestration, memory/RAG, models, evals, or security boundaries.
- Reliability, latency, cost, governance, or silent failures surfaced after the demo.
- A rewrite, vendor, hire, or quarter of engineering work needs a second read.
What I Review
- Architecture: boundaries, orchestration, tools, permissions, escalation.
- Reliability: evals, observability, incident paths, silent failures.
- Context: RAG quality, memory, state, retrieval, integration handoffs.
- Production: durable execution, retries, recovery, latency, security.
- Economics: model choice, routing, inference cost, build vs. buy.
- Operating model: ownership, reviewer capacity, roadmap authority, and vendor accountability.
Choose the Right Path
| Decision State | What Is Missing | Right Path |
|---|---|---|
| Need a bounded answer | One AI workflow needs a principal review before the next commitment. | Production AI Readiness Review |
| Need recurring review or delivery | Your technical lead needs ongoing review, or the team needs builders. | Technical Advisory; implementation and broader leadership scoped separately |
| Strong internal owner | A named principal has authority, time, and review capacity. | Keep internal; use Concepts and Patterns |
What the Review Produces
- Decision: what to keep, change, or investigate.
- Path: stay internal, commission a readiness review, add ongoing advisory, or build.
- Rationale: tradeoffs the team can defend and operate before the system gets harder to move.
Compare the Engagements
See current scope, pricing, and intake on the advisory brief.