Infrastructure
AI-native stack for operational systems
Representative layers across model interfaces, orchestration, retrieval, automation, services, and platform envelopes. Not a resume list: the stack is organized around runtime behavior.
Stack layers
Infrastructure map
STACK.LLM
LLM Systems
Inference surfaces, routing discipline, and model lifecycle hygiene.
- OpenAI · Gemini · multi-provider routing
- Structured outputs & tool schemas
- Latency / spend envelopes
- Eval traces & prompt revisioning
STACK.AGT
Agent Frameworks
Orchestration primitives that survive ambiguity and partial failures.
- LangChain & composable tools
- Planner · executor separation
- Human-in-the-loop checkpoints
- Retries, backoff, cancellation
STACK.RTR
Retrieval & Memory
Grounded answers via ingestion geometry—not vibes.
- Chunking · embeddings · rerank
- PostgreSQL / pgvector paths
- Session vs durable memory tiers
- Attribution-friendly citations
STACK.AUT
Automation
Event-native workloads beside critical synchronous paths.
- n8n · webhook choreography
- Cron & deferred queues
- Idempotent side-effects
- Audit trails across hops
STACK.BE
Backend
Services that stay observable under orchestrated AI traffic.
- Node.js · TypeScript services
- PostgreSQL · transactional cores
- REST · typed RPC boundaries
- Background workers
STACK.INF
Infrastructure
Reliability, delivery, and cost posture at platform depth.
- GCP · containers · IaC-ready layouts
- Dockerized builds
- CI/CD · progressive rollout patterns
- Logging · metrics · AI-call telemetry hooks