Topics
Explore by engineering domain
AI engineering, databases, cloud platforms, system design, fundamentals, and field notes.
AI Engineering
Agents, context engineering, harness design, MCP, evaluation, token efficiency, and AI-assisted engineering workflows.
- Agentic RAG: When Natural Language Search Becomes an Action System
- Retrieve, Constrain, Verify, Abstain: A Near-Zero Hallucination RAG Architecture, Reviewed
- The Agentic Orchestration Layer: Scaling Database Operations from Sailor to Captain
Databases
PostgreSQL, Aurora, MySQL, Oracle, Cassandra, MongoDB, pgvector, replication, migrations, indexing, and database operations.
- Embedding Backfill in Postgres: Batch Size, WAL, Autovacuum, and Bloat
- pgvector Backup and Restore: Why Embeddings Change Your RPO/RTO Thinking
- pgvector on Aurora PostgreSQL: What DBAs Need to Watch
Cloud & Platform
AWS, Azure, GCP, OCI, Terraform, Kubernetes, CI/CD, Cloudflare, developer platforms, and operational control planes.
- The Math Behind Database Reserved Instances: When to Wait
- BigQuery Cost Optimization: On-Demand vs Slot Commitments
- Database Licensing Cost Across AWS, Azure, GCP, and OCI
System Design
Architecture reviews, scalability, failure modes, guardrails, distributed systems, reliability boundaries, and production tradeoffs.
- Why Your Non-Prod Databases Cost as Much as Production
- 330 Redundant Data Centers All Failed Simultaneously — Because They Were Identical
- The End of Single-Signal Alerting: Correlating Metrics, Logs, Traces, Deployments, and Cost
Engineering Fundamentals
Core engineering principles, debugging workflows, observability, performance basics, reviews, and practical operating habits.
- AI Cost Observability Dashboard: LangSmith vs Helicone
- Alert Fatigue Engineering: How to Build Fewer, Better, Actionable Alerts
- Cost Observability: Build Dashboards That Show Waste Before Finance Finds It
Field Notes
Short practical observations, checklists, production lessons, debugging notes, and decision patterns from real engineering work.
- From POC to Production: A Natural Language Search Migration Playbook
- GraphRAG: Use It When Relationships Matter, Not When Search Is Hard
- Agentic RAG: When Natural Language Search Becomes an Action System