Architecture breakdowns
Clear views of system boundaries, trade-offs, and the decisions that matter after a prototype works.
02 / Coverage
The practical enterprise AI stack.
Coverage follows the architecture—not the hype cycle.
- 01
Enterprise RAG
Retrieval quality, evaluation, permissions, grounding, indexing, and operational design.
- 02
Agents and agentic systems
Orchestration, tool use, control boundaries, failure modes, and where agents are actually useful.
- 03
LLM evaluation and observability
Quality measurement, traces, test sets, monitoring, and production feedback loops.
- 04
AI architecture
System boundaries, platform choices, security, governance, and integration with existing estates.
- 05
Enterprise data platforms
Snowflake Cortex and other platform capabilities when they change implementation choices.
- 06
Production patterns
Reliability, latency, cost, deployment, incident readiness, and operational ownership.
- 07
Models and tools
New capabilities examined for practical impact rather than launch-day novelty.
Example issue structure
Format previewEvaluating enterprise RAG beyond answer quality
The engineering problem
Frame why end-to-end answer scoring alone can hide retrieval failures, permission gaps, and weak evidence.
The architecture view
Separate retrieval, ranking, context assembly, generation, and policy checks into observable evaluation boundaries.
The implementation pattern
Connect test sets, component metrics, traces, and review workflows into a repeatable engineering loop.
Production notes
Close with operational trade-offs, failure modes, and concrete questions for the next design review.