Case studies
Integrating an LLM Without Letting It Own Your Architecture
Adding an LLM-powered feature while keeping it a swappable component — API abstraction, timeout handling, output validation, and prompt versioning.
One Database, Five Products: Designing Multi-Tenancy Without a Framework
How we isolated five client products in a single PostgreSQL database using row-level tenant_id and shared schema — and why we skipped off-the-shelf multi-tenant frameworks.
Cost Control for AI-Backed Features: Token Budgets and Semantic Caching
Reducing LLM API spend without degrading UX — semantic caching, per-tenant token budgets, and model selection by task complexity.
When to Cache and When to Query: Drawing the Line with Redis and PostgreSQL
Defining a caching strategy for a multi-tenant platform — what to cache, when to invalidate, and when to always hit the database.
Designing a Human-in-the-Loop Review Pipeline
Building a pipeline where AI generates first drafts and humans review before content reaches users — job queues, confidence thresholds, and feedback loops.
From Manual Deploys to Push-and-Ship: Building a CI/CD Pipeline for a Small Team
Replacing manual SSH deploys with a Docker-based pipeline on GitHub Actions and AWS — and what we learned about rollbacks and environment parity.
Splitting the Monolith Before It Hurts: Service Boundaries in a Growing Platform
Identifying the first service boundary to extract from our monolith — and how we drew the line without over-engineering.
Securing a Multi-Tenant Platform: Where Auth Meets Data Isolation
Enforcing tenant boundaries at every layer — JWT with tenant claims, middleware validation, audit logging, and defense in depth.
Designing for Failure: What Happens When Your API Layer Goes Down
Adding resilience to a client app that depended on a flaky third-party API — circuit breakers, retries, and graceful degradation.
Background Jobs That Don't Bring Down the Main App
Extracting heavy work to a worker process — job queues, priority levels, dead letter handling, and resource isolation.
Why I Chose a Monolith (and When I'd Break It Apart)
Deliberately building a monolith for a side project — and the criteria I'd use to split it into services later.
The Schema That Survived Three Pivots
How a flexible data model held up across three major product pivots — and what made it resilient.
Multi-Region, Single Brain: Designing for Low Latency Across Geographies
Serving users globally without splitting the source of truth — CDN, read replicas, edge caching, and write-path routing.
Zero to Observable: Adding Monitoring to a System That Had None
Introducing Grafana and Prometheus to a system with no visibility — what we measured first, and what we learned about debugging with data.