Backend articles
Reliable services and APIs that hold up as a product grows - data, boundaries, and infrastructure you can actually operate.
Agentic commerce: how an AI agent proves you agreed to buy
AI agents are checking out on your behalf. The hard part was never moving the money - it's proving consent. How signed mandates make intent verifiable.
Why Postgres falls over at 200 connections
Postgres gives every connection its own operating-system process. That one fact explains the crash, why raising the limit backfires, and what a pooler fixes.
How DynamoDB actually works
A complete explanation: what a partition key really does, why 3,000 reads is the number that matters, how to design a schema, and when not to use it.
Redis, explained simply
Redis is memory that optionally persists. Out of the box it won't evict anything and can lose minutes of writes in a crash. Here's what to set instead.
Supabase, explained simply
What Supabase actually is, what it costs, the one security concept you must understand, and an honest list of when to use it - and when not to.
Multi-tenancy: how to choose before it's expensive to change
Shared schema, database-per-tenant, or sharded? The deciding factor isn't cost - it's what happens when one customer needs something the others don't.
MCP is stateless now: what the 2026-07-28 spec changes
The new MCP spec deletes the initialize handshake, sessions, and resumable streams. Your server becomes an ordinary HTTP service - and scales like one.
Background agents: AI that finishes the job after you close the tab
Agents now run for hours at coin-flip reliability. That's why AI is moving from the chat box to durable background workflows that survive crashes and retries.
Just use Postgres: one database instead of five
Postgres plus a few extensions now covers search, vectors, queues, documents, and jobs. Add a specialized system only when a real bottleneck forces it.
Designing a backend an AI agent can actually use
Agents retry, chain, and act unsupervised - so APIs built for humans break. Idempotency, structured errors, and observability make a backend agent-ready.
You probably don't need a vector database
The AI wave pushed everyone toward a dedicated vector database. For most apps, Postgres with pgvector does the job - one fewer system to run, secure, and sync.
Your API needs an MCP server (and it's a security boundary)
AI agents are a new class of API consumer, and MCP is how they call your backend. The interesting work isn't the tools - it's auth, scoping, and audit.
How to design an API that lasts (2026)
How to design an API that survives real use: REST vs GraphQL, versioning from day one, and the backward-compatibility rules that stop you breaking clients.
Node.js vs NestJS in 2026: choosing your backend stack
Node.js vs NestJS in 2026: NestJS runs on Node, it's not an alternative. When raw Express is right, when NestJS earns its structure, and where Fastify fits.
SQL vs NoSQL in 2026: how to choose (start with Postgres)
SQL vs NoSQL in 2026: why Postgres is the safe default, when a document database actually wins, and how to choose without regretting it later.